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Citation: Küçüktopçu, E.; Cemek, B.;
Simsek, H. Modeling Environmental
Conditions in Poultry Production:
Computational Fluid Dynamics
Approach. Animals 2024,14, 501.
https://doi.org/10.3390/ani14030501
Academic Editor: Alessandro Dal
Bosco
Received: 12 December 2023
Revised: 27 January 2024
Accepted: 1 February 2024
Published: 2 February 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
animals
Review
Modeling Environmental Conditions in Poultry Production:
Computational Fluid Dynamics Approach
Erdem Küçüktopçu 1, * , Bilal Cemek 1and Halis Simsek 2
1Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Türkiye;
bcemek@omu.edu.tr
2Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA;
simsek@purdue.edu
*Correspondence: erdem.kucuktopcu@omu.edu.tr
Simple Summary: The aim of this review is to provide researchers with a guide to simulating the
environment of poultry houses using computational fluid dynamics. Through an extensive review of
the literature in this area, it provides comprehensive insights into the common challenges encountered
when applying this method, as well as a discussion of planned future research efforts.
Abstract: In recent years, computational fluid dynamics (CFD) has become increasingly important and
has proven to be an effective method for assessing environmental conditions in poultry houses. CFD
offers simplicity, efficiency, and rapidity in assessing and optimizing poultry house environments,
thereby fueling greater interest in its application. This article aims to facilitate researchers in their
search for relevant CFD studies in poultry housing environmental conditions by providing an
in-depth review of the latest advancements in this field. It has been found that CFD has been
widely employed to study and analyze various aspects of poultry house ventilation and air quality
under the following five main headings: inlet and fan configuration, ventilation system design, air
temperature–humidity
distribution, airflow distribution, and particle matter and gas emission. The
most commonly used turbulence models in poultry buildings are the standard k-
ε
, renormalization
group (RNG) k-
ε
, and realizable k-
ε
models. Additionally, this article presents key solutions with
a summary and visualization of fundamental approaches employed in addressing path planning
problems within the CFD process. Furthermore, potential challenges, such as data acquisition,
validation, computational resource requirements, meshing, and the selection of a proper turbulence
model, are discussed, and avenues for future research (the integration of machine learning, building
information modeling, and feedback control systems with CFD) are explored.
Keywords: broiler; airflow; microclimate; simulation
1. Introduction
The global population, which stands at approximately 8 billion, is projected to reach
nearly 10 billion by 2050 [
1
]. Meeting the food requirements of this expanding population
requires a dual focus on increasing production capacities and improving production qual-
ity [
2
,
3
]. The ultimate objective is to achieve larger yields of superior-quality products per
unit of agricultural land. This imperative has led to the widespread adoption of cutting-
edge production techniques, including automation and mechanization systems [4–6].
With the application of these new technologies in livestock production, the global
poultry market has experienced continuous growth, with production volumes rising from
97.32 million tons in 2019 to 102.04 million tons in 2022 [
7
]. This growth is primarily
driven by the contributions of countries, such as the USA, Brazil, and China, with notable
advancements also observed in Thailand, Mexico, and Türkiye [
8
]. It is further anticipated
to increase by approximately 76% in 2050, reaching 180 million tons [9].
Animals 2024,14, 501. https://doi.org/10.3390/ani14030501 https://www.mdpi.com/journal/animals
Animals 2024,14, 501 2 of 21
To ensure adequate food supplies for the growing population, it is critical to focus
on modernizing poultry production. This includes advances in genetic breeding research
and providing optimal environmental conditions for the birds. While much attention has
been paid to breeding and feeding research in efforts to increase poultry production and
productivity [
10
–
12
], it is important to acknowledge that the desired level of productivity
cannot be achieved without appropriate environmental conditions in poultry houses [
13
].
Therefore, planning and designing poultry houses that provide optimal environmental
conditions are imperative.
Effective planning and design of poultry houses involve a meticulous consideration
of both the ideal indoor environmental conditions and the local climate data at the loca-
tion [
14
]. The welfare and productivity of birds are closely intertwined with their immediate
environment. It is, therefore, essential to create an environment that is conducive to their
well-being and optimum performance. Failure to provide ideal conditions during the
brooding phase can lead to reduced profitability, slower growth of birds, decreased feed
intake, and increased disease susceptibility and mortality [
15
]. Historical data reveal the
importance of providing an optimal housing climate. In the 1920s, the average mortality
rate for broilers was about 20%. With advances in nutrition, house quality, and disease
control methods, the mortality rate decreased by 4% by the end of the 20th century [
16
].
These experiences highlight the importance of providing an optimal indoor environment
in poultry houses.
The assessment of environmental conditions within a poultry house can be signifi-
cantly enhanced by applying modeling techniques. The models are specifically designed to
simulate real-world scenarios using simplified approaches that deepen our comprehension
of these situations and enable more accurate predictions for the future. In these models,
heat and mass balance equations are solved to determine the factors, including animal
species and age, building characteristics, and indoor and ambient conditions. These equa-
tions, which cannot be solved directly using analytical methods, are effectively tackled
through numerical methods, such as computational fluid dynamics (CFD) [17,18].
Although numerous CFD studies have examined environmental conditions in various
animal buildings, none have offered a comprehensive review that presents the current
state-of-the-art research and development concerning environmental conditions in poultry
buildings. Therefore, the primary objective of this review is to fill this gap by discussing
the potential applications of CFD in evaluating poultry building environmental conditions.
Additionally, it aims to address the existing challenges and recent advancements in physical
models and numerical techniques within a typical commercial CFD workbench.
This review emphasizes the critical importance of realism in CFD simulations and
highlights the need for CFD modelers to address specific challenging issues. Furthermore,
it explores various modeling techniques that can enhance the accuracy of CFD solutions for
poultry building environments.
2. Importance of Environmental Assessment in Poultry Houses
Ensuring optimal air quality in poultry houses is crucial for the well-being of birds,
with air temperature, humidity, velocity, and pollutant concentrations (Figure 1) being the
key factors to consider [
19
]. To meet their requirements, a well-functioning ventilation
system should maintain a continuous airflow, providing sufficient oxygen, appropriate
humidity, velocity, and temperature while effectively removing gaseous pollutants. During
summer, when external weather conditions are hot and humid, the temperature and
humidity inside the poultry house tend to exceed the recommended ranges, leading to heat
stress among the birds. This heat stress remains a prominent challenge in poultry farming.
In a broiler house, it is recommended to initially set the indoor air temperatures
between 30 and 33
◦
C and gradually decrease them to 24–26
◦
C over a period of 3–4 weeks.
By the time 5–6 weeks have passed, the temperatures should be further reduced to a range
of 18–21 ◦C [19,20].
Animals 2024,14, 501 3 of 21
Animals2024,14,xFORPEERREVIEW3of21
Figure1.Environmentalfactorsaffectingthebroilers’performance.
Inabroilerhouse,itisrecommendedtoinitiallysettheindoorairtemperaturesbe-
tween30and33°Candgraduallydecreasethemto24–26°Coveraperiodof3–4weeks.
Bythetime5–6weekshavepassed,thetemperaturesshouldbefurtherreducedtoarange
of18–21°C[19,20].
Highhumiditylevelsinpoultryhousescanhavedetrimentaleffectsonthewell-be-
ingandgrowthofthebirds[13].Totacklethisissue,itiscrucialtoimplementadequate
ventilationandtemperaturecontrolstrategies.Duringthesummerseason,increasing
ventilationratescaneffectivelyremovemoistureandreducehumidity.Duringwinter,
raisingindoorairtemperaturethroughheatsourcescanresultinareductioninrelative
humidity.Forthefirstthreedaysofabird’slife,relativehumidityof65–70%isrecom-
mended,ashumiditybelow50%canleadtodehydrationinchicks.Afterthreedays,in-
doorairhumidityshouldrangefrom50%to70%,consideringthetemperatureandbird
conditions[21,22].
Ensuringaconsistentairvelocitythroughouttheanimal-occupiedzone(AOZ)iscru-
cialtopreventanimalsfrommigratingtoareaswithbeerventilation.Theconcentration
ofbirdsinspecificareaswithimprovedairflowcanleadtoheightenedmortalityrates.
Maintaininganairvelocityofapproximately0.3ms
−1
duringthefirsttwoweeksisgen-
erallyrecommended,increasingto0.5ms
−1
inthethirdweek,1ms
−1
inthefourthweek,
andabove1ms
−1
afterward[23–25].Inhotweatherconditions,whentemperaturesare
elevated,ahigherairvelocityofapproximately2.5ms
−1
isnecessarytoprovideadequate
coolingforthechickens[26].
Thepresenceoftoxicgases,includingcarbondioxide(CO
2
),ammonia(NH
3
),carbon
monoxide(CO),andhydrogensulfide(H
2
S),inpoultryfarmsadverselyaffectsbirdper-
formanceandhealthofbirds.Birdscantoleratepollutantgasesuptocertainconcentra-
tions,withthemaximumallowablelevelsof3000ppmforCO
2
,20ppmforNH
3
,10ppm
forCO,and0.5ppmforH
2
S[16].
3.VentilationSystemsforPoultryHouses
Effectiveventilationisacornerstoneforsuccessfullymanagingtheenvironmental
conditionswithinpoultryhouses[27].Itsparamountimportanceliesinitsroleasakey
factorinalleviatingrespiratoryproblemsinthebirds,therebypromotingoptimalproduc-
tivityandachievingthehighestconversionrates.
Ventilationstrategiesforpoultryhousesrangefromfullynaturalventilation(NV)to
fullymechanicalventilation(MV)andhybridnatural–mechanicalventilation(NMV).
WithNV,thebuildingdesignincludescontrolledsidewallcurtainsandridgevents.
TheNMVmethodwasdevelopedtoreplacetheNVactionspecificallyincold
weather,withtheaimofimprovingcontroloverthethermalenvironment.Forwarmand
Figure 1. Environmental factors affecting the broilers’ performance.
High humidity levels in poultry houses can have detrimental effects on the well-being
and growth of the birds [
13
]. To tackle this issue, it is crucial to implement adequate ventila-
tion and temperature control strategies. During the summer season, increasing ventilation
rates can effectively remove moisture and reduce humidity. During winter, raising indoor
air temperature through heat sources can result in a reduction in relative humidity. For the
first three days of a bird’s life, relative humidity of 65–70% is recommended, as humidity
below 50% can lead to dehydration in chicks. After three days, indoor air humidity should
range from 50% to 70%, considering the temperature and bird conditions [21,22].
Ensuring a consistent air velocity throughout the animal-occupied zone (AOZ) is
crucial to prevent animals from migrating to areas with better ventilation. The concentration
of birds in specific areas with improved airflow can lead to heightened mortality rates.
Maintaining an air velocity of approximately 0.3 m s
−1
during the first two weeks is
generally recommended, increasing to 0.5 m s
−1
in the third week, 1 m s
−1
in the fourth
week, and above 1 m s
−1
afterward [
23
–
25
]. In hot weather conditions, when temperatures
are elevated, a higher air velocity of approximately 2.5 m s
−1
is necessary to provide
adequate cooling for the chickens [26].
The presence of toxic gases, including carbon dioxide (CO
2
), ammonia (NH
3
), carbon
monoxide (CO), and hydrogen sulfide (H
2
S), in poultry farms adversely affects bird perfor-
mance and health of birds. Birds can tolerate pollutant gases up to certain concentrations,
with the maximum allowable levels of 3000 ppm for CO
2
, 20 ppm for NH
3
, 10 ppm for CO,
and 0.5 ppm for H2S [16].
3. Ventilation Systems for Poultry Houses
Effective ventilation is a cornerstone for successfully managing the environmental
conditions within poultry houses [
27
]. Its paramount importance lies in its role as a
key factor in alleviating respiratory problems in the birds, thereby promoting optimal
productivity and achieving the highest conversion rates.
Ventilation strategies for poultry houses range from fully natural ventilation (NV) to
fully mechanical ventilation (MV) and hybrid natural–mechanical ventilation (NMV). With
NV, the building design includes controlled side wall curtains and ridge vents.
The NMV method was developed to replace the NV action specifically in cold weather,
with the aim of improving control over the thermal environment. For warm and hot
weather ventilation, the system relies on the opening of sidewall curtains and natural wind,
while maintaining the same basic orientation requirements as a NV building. This strategic
approach allows for greater adaptability to different weather conditions while ensuring
efficient management of the indoor environment. The NMV method eliminates the need
Animals 2024,14, 501 4 of 21
for cold weather ridge vents. Therefore, this method often utilizes a flat internal ceiling
along with a heavily insulated attic for optimal thermal regulation [28].
In modern intensive poultry houses, an MV system with negative pressure is generally
used. This system usually consists of exhaust fans connected in parallel, and fresh air is
drawn in through the ceiling air outlets in cold to mild temperatures. In warmer to hot
temperatures, on the other hand, the fresh air supply is facilitated by side wall and/or end
wall curtains. The negative pressure MV system operates by creating a pressure differential
inside the house, allowing air to flow from the inside to the outside. This configuration
allows for efficient control of ventilation, temperature, and air quality [29].
4. Heating Systems for Poultry House
Poultry farms generally use two primary supplementary heating methods, radiant
heaters and forced air space heaters, to ensure optimal environmental conditions for chick
rearing [
30
,
31
]. The difference between these two methods lies in the way they deliver heat
into the space.
Space heaters with forced ventilation heat the air in the building [
31
]. Although they
have been used in the past, the recent trend in the poultry industry shows a move away
from these heaters. The reason for this move is the observation that forced air heaters
cannot effectively conduct heat to the floor, which is essential for warming the litter and
thus maintaining an environment conducive to chick welfare.
In contrast, radiant heaters are an alternative that has gained popularity due to their
effectiveness in directly heating the birds and the litter [
32
]. These heaters radiate heat
energy and offer a more targeted and efficient way of warming the floor.
5. Fundamentals of CFD
To conduct a CFD analysis, the analyst initiates the process by formulating the problem
and employing scientific expertise to articulate it mathematically. Subsequently, the CFD
software package incorporates this knowledge, translating the stated problem into scientific
terms. Finally, the computer executes the calculations provided by the CFD software, and
the analyst reviews and interprets the results [
33
]. The CFD analysis consists of three main
steps: pre-processing, processing, and post-processing (Figure 2).
Animals2024,14,xFORPEERREVIEW4of21
hotweatherventilation,thesystemreliesontheopeningofsidewallcurtainsandnatural
wind,whilemaintainingthesamebasicorientationrequirementsasaNVbuilding.This
strategicapproachallowsforgreateradaptabilitytodifferentweatherconditionswhile
ensuringefficientmanagementoftheindoorenvironment.TheNMVmethodeliminates
theneedforcoldweatherridgevents.Therefore,thismethodoftenutilizesaflatinternal
ceilingalongwithaheavilyinsulatedaicforoptimalthermalregulation[28].
Inmodernintensivepoultryhouses,anMVsystemwithnegativepressureisgener-
allyused.Thissystemusuallyconsistsofexhaustfansconnectedinparallel,andfreshair
isdrawninthroughtheceilingairoutletsincoldtomildtemperatures.Inwarmertohot
temperatures,ontheotherhand,thefreshairsupplyisfacilitatedbysidewalland/orend
wallcurtains.ThenegativepressureMVsystemoperatesbycreatingapressuredifferen-
tialinsidethehouse,allowingairtoflowfromtheinsidetotheoutside.Thisconfiguration
allowsforefficientcontrolofventilation,temperature,andairquality[29].
4.HeatingSystemsforPoultryHouse
Poultryfarmsgenerallyusetwoprimarysupplementaryheatingmethods,radiant
heatersandforcedairspaceheaters,toensureoptimalenvironmentalconditionsforchick
rearing[30,31].Thedifferencebetweenthesetwomethodsliesinthewaytheydeliver
heatintothespace.
Spaceheaterswithforcedventilationheattheairinthebuilding[31].Althoughthey
havebeenusedinthepast,therecenttrendinthepoultryindustryshowsamoveaway
fromtheseheaters.Thereasonforthismoveistheobservationthatforcedairheaterscan-
noteffectivelyconductheattothefloor,whichisessentialforwarmingthelierandthus
maintaininganenvironmentconducivetochickwelfare.
Incontrast,radiantheatersareanalternativethathasgainedpopularityduetotheir
effectivenessindirectlyheatingthebirdsandthelier[32].Theseheatersradiateheat
energyandofferamoretargetedandefficientwayofwarmingthefloor.
5.FundamentalsofCFD
ToconductaCFDanalysis,theanalystinitiatestheprocessbyformulatingtheprob-
lemandemployingscientificexpertisetoarticulateitmathematically.Subsequently,the
CFDsoftwarepackageincorporatesthisknowledge,translatingthestatedprobleminto
scientificterms.Finally,thecomputerexecutesthecalculationsprovidedbytheCFDsoft-
ware,andtheanalystreviewsandinterpretstheresults[33].TheCFDanalysisconsistsof
threemainsteps:pre-processing,processing,andpost-processing(Figure2).
Figure2.ComputationprocedureofaCFDsimulation.
Figure 2. Computation procedure of a CFD simulation.
5.1. Pre-Processing
The simulation relies on thorough problem analysis, which is critical to defining pre-
cise goals and parameters and fully understanding the underlying problems. Defining
the physics of the problem forms the foundation, followed by creating a problem-specific
two- or three-dimensional geometry for accurate problem analysis. The final step of pre-
processing is then discretization or meshing. Figure 3shows an example, which is the
Animals 2024,14, 501 5 of 21
meshing structure of a commercial broiler house [
34
]. The continuous fluid domain is
subdivided into smaller, discrete control volumes or cells. This subdivision can be per-
formed using a variety of techniques, such as structured grids or unstructured meshes. The
choice of meshing technique depends on the nature of the problem and the computational
resources available. Once the meshing is complete, the boundaries of the problem domain
can be determined, and the required boundary conditions defined in the initial phase can
be applied.
Animals2024,14,xFORPEERREVIEW5of21
5.1.Pre-Processing
Thesimulationreliesonthoroughproblemanalysis,whichiscriticaltodefiningpre-
cisegoalsandparametersandfullyunderstandingtheunderlyingproblems.Definingthe
physicsoftheproblemformsthefoundation,followedbycreatingaproblem-specifictwo-
orthree-dimensionalgeometryforaccurateproblemanalysis.Thefinalstepofpre-pro-
cessingisthendiscretizationormeshing.Figure3showsanexample,whichisthemesh-
ingstructureofacommercialbroilerhouse[34].Thecontinuousfluiddomainissubdi-
videdintosmaller,discretecontrolvolumesorcells.Thissubdivisioncanbeperformed
usingavarietyoftechniques,suchasstructuredgridsorunstructuredmeshes.Thechoice
ofmeshingtechniquedependsonthenatureoftheproblemandthecomputationalre-
sourcesavailable.Oncethemeshingiscomplete,theboundariesoftheproblemdomain
canbedetermined,andtherequiredboundaryconditionsdefinedintheinitialphasecan
beapplied.
Figure3.Meshingstructureofacommercialbroilerhouse
[34]
.
5.2.Processing
Processinginvolvesusingacomputertosolvethemathematicalequationsoffluid
flow.Oncethedomainisdiscretized,theanalysisisperformedforeachcontrolvolume.
Thegoverningequations,suchastheNavier–Stokesequationsforfluidflow,areapplied
toeachcontrolvolumetoestablishasystemofequations.Theseequationsdescribethe
conservationofmass(Equation(1)),momentum(Equation(2)),andenergy(Equation(3))
ineachvolume.
Conservationofmass(continuityequation):Thenetmassflowintooroutofacontrol
volumemustbebalanced.
0
j
j
u
tx
(1)
Conservationofmomentum(momentumequation):Thesumofexternalforcesact-
ingonafluidparticleequalstherateofchangeinitslinearmomentum.
j
i
jij ij i
jj ji
u
u
uuu p g
tx x xx
(2)
Figure 3. Meshing structure of a commercial broiler house [34].
5.2. Processing
Processing involves using a computer to solve the mathematical equations of fluid
flow. Once the domain is discretized, the analysis is performed for each control volume.
The governing equations, such as the Navier–Stokes equations for fluid flow, are applied
to each control volume to establish a system of equations. These equations describe the
conservation of mass (Equation (1)), momentum (Equation (2)), and energy (Equation (3))
in each volume.
Conservation of mass (continuity equation): The net mass flow into or out of a control
volume must be balanced. ∂ρ
∂t+∂
∂xjρuj=0 (1)
Conservation of momentum (momentum equation): The sum of external forces acting
on a fluid particle equals the rate of change in its linear momentum.
∂
∂tρuj+∂
∂xjρuiuj=∂
∂xj"−pδij +µ ∂ui
∂xj
+∂uj
∂xi!#+ρgi(2)
Conservation of energy (energy equation): The rate of change in the energy of a fluid
particle equals the sum of heat addition and work performed on the particle.
∂
∂t(ρCaT)+∂
∂xjρujCaT−∂
∂xj λ∂T
∂xj!=ST(3)
where
ρ
: density (kg m
−3
), t: time (s), x: Cartesian coordinates (m), u: velocity component
(m s
−1
), p: pressure (Pa),
δ
: Kronecker delta,
µ
: dynamic viscosity (kg m
−1
s
−1
), g: accelera-
tion due to gravity (m s
−2
), C
a
: specific heat capacity (W kg
−1
K
−1
), T: temperature (K),
λ
:
Animals 2024,14, 501 6 of 21
thermal conductivity (W m
−1
K
−1
), S
T
: thermal sink or source (W m
−3
), and Iand j: the
Cartesian coordinate index.
In this step, it is necessary to refer to some turbulence models. A bewildering variety of
such models can be found in the literature, the two main classes being Reynolds-averaged
Navier–Stokes models (RANS) and large eddy simulation (LES). The choice of turbulence
model depends on the specific flow problem, the available computational resources, and
the desired level of accuracy [
35
]. Engineers select an appropriate turbulence model based
on the flow characteristics, Reynolds number, boundary conditions, and analysis objectives.
After determining the appropriate turbulence model, numerical methods are used to
iteratively solve the equations, often using finite difference, finite volume, or finite element
methods. These methods provide solutions at discrete points within each control volume,
known as nodes. These solutions provide valuable information about the fluid variables at
these locations, such as velocity, pressure, temperature, and species concentration.
5.3. Post-Processing
Once the simulation phase produces results, the next step is to analyze them. Various
methods can be used for this analysis, including vector plots, contour plots, data curves,
and streamlines. These graphical representations often employ colors to distinguish be-
tween different value ranges. For example, Figure 4illustrates airspeed (m s
−1
) contours
in different planes within a commercial broiler house during the summer [
36
]. These
visualizations help grasp the distribution of airspeed within the enclosed environment.
Animals2024,14,xFORPEERREVIEW6of21
Conservationofenergy(energyequation):Therateofchangeintheenergyofafluid
particleequalsthesumofheatadditionandworkperformedontheparticle.
aja T
jjj
T
CT uCT S
tx xx
(3)
whereρ:density(kgm−3),t:time(s),x:Cartesiancoordinates(m),u:velocitycomponent
(ms−1),p:pressure(Pa),δ:Kroneckerdelta,µ:dynamicviscosity(kgm−1s−1),g:acceleration
duetogravity(ms−2),Ca:specificheatcapacity(Wkg−1K−1),T:temperature(K),λ:thermal
conductivity(Wm−1K−1),ST:thermalsinkorsource(Wm−3),andIandj:theCartesian
coordinateindex.
Inthisstep,itisnecessarytorefertosometurbulencemodels.Abewilderingvariety
ofsuchmodelscanbefoundintheliterature,thetwomainclassesbeingReynolds-aver-
agedNavier–Stokesmodels(RANS)andlargeeddysimulation(LES).Thechoiceoftur-
bulencemodeldependsonthespecificflowproblem,theavailablecomputationalre-
sources,andthedesiredlevelofaccuracy[35].Engineersselectanappropriateturbulence
modelbasedontheflowcharacteristics,Reynoldsnumber,boundaryconditions,and
analysisobjectives.Afterdeterminingtheappropriateturbulencemodel,numericalmeth-
odsareusedtoiterativelysolvetheequations,oftenusingfinitedifference,finitevolume,
orfiniteelementmethods.Thesemethodsprovidesolutionsatdiscretepointswithineach
controlvolume,knownasnodes.Thesesolutionsprovidevaluableinformationaboutthe
fluidvariablesattheselocations,suchasvelocity,pressure,temperature,andspeciescon-
centration.
5.3.Post-Processing
Oncethesimulationphaseproducesresults,thenextstepistoanalyzethem.Vari o us
methodscanbeusedforthisanalysis,includingvectorplots,contourplots,datacurves,
andstreamlines.Thesegraphicalrepresentationsoftenemploycolorstodistinguishbe-
tweendifferentvalueranges.Forexample,Figure4illustratesairspeed(ms−1)contoursin
differentplaneswithinacommercialbroilerhouseduringthesummer[36].Thesevisual-
izationshelpgraspthedistributionofairspeedwithintheenclosedenvironment.
Figure4.Airspeedcontoursinacommercialbroilerhouseduringsummer[36].
6.AdvantagesandLimitationsofUsingCFD
CFDoffersadualperspectivewithnotableadvantagesandinherentlimitations.On
thepositiveside,itservesasacost-efficientandtime-savingalternativetotraditionalex-
perimentalmethods.Itallowstheexplorationofdifferentscenariosanddesigniterations
inavirtualenvironment.TheabilityofCFDtoprovidedetailedinsightsintofluid
Figure 4. Airspeed contours in a commercial broiler house during summer [36].
6. Advantages and Limitations of Using CFD
CFD offers a dual perspective with notable advantages and inherent limitations. On
the positive side, it serves as a cost-efficient and time-saving alternative to traditional
experimental methods. It allows the exploration of different scenarios and design iterations
in a virtual environment. The ability of CFD to provide detailed insights into fluid dynamics,
pressure, and temperature in simulated areas provides engineers with valuable data for
design optimization. It also enables analysis of the hard-to-reach regions, helping to identify
problems early in the design phase [
37
]. However, there are limitations, mainly related
to the accuracy of the mathematical models and the dependency on the mesh [
38
]. The
validity of CFD results depends on accurate models, and the dependence on the quality
and size of the mesh can be challenging. Complex simulations often require significant
computing resources, which limits access to high-performance computers. In addition,
user expertise is critical, as incorrect applications and simplifying assumptions can lead to
inaccurate conclusions. Despite these limitations, using CFD with experimental validation
remains a practical approach for understanding and optimizing fluid dynamics in various
engineering applications.
Animals 2024,14, 501 7 of 21
7. Role of CFD in Environmental Assessment
Air distribution in an enclosed environment can be influenced by different forces,
including natural wind, mechanical fans, and thermal buoyancy. The complex airflow pat-
terns, including circulation, reattachment, separation, vortex impingement, and buoyancy
effects, are a result of these forces interacting with each other and with the geometry of the
enclosed space, as illustrated in Figure 5[39].
Animals2024,14,xFORPEERREVIEW7of21
dynamics,pressure,andtemperatureinsimulatedareasprovidesengineerswithvaluable
datafordesignoptimization.Italsoenablesanalysisofthehard-to-reachregions,helping
toidentifyproblemsearlyinthedesignphase[37].However,therearelimitations,mainly
relatedtotheaccuracyofthemathematicalmodelsandthedependencyonthemesh[38].
ThevalidityofCFDresultsdependsonaccuratemodels,andthedependenceonthequal-
ityandsizeofthemeshcanbechallenging.Complexsimulationsoftenrequiresignificant
computingresources,whichlimitsaccesstohigh-performancecomputers.Inaddition,
userexpertiseiscritical,asincorrectapplicationsandsimplifyingassumptionscanlead
toinaccurateconclusions.Despitetheselimitations,usingCFDwithexperimentalvalida-
tionremainsapracticalapproachforunderstandingandoptimizingfluiddynamicsin
variousengineeringapplications.
7.RoleofCFDinEnvironmentalAssessment
Airdistributioninanenclosedenvironmentcanbeinfluencedbydifferentforces,
includingnaturalwind,mechanicalfans,andthermalbuoyancy.Thecomplexairflowpat-
terns,includingcirculation,reaachment,separation,vorteximpingement,andbuoyancy
effects,arearesultoftheseforcesinteractingwitheachotherandwiththegeometryof
theenclosedspace,asillustratedinFigure5[39].
Theflowregimewithinanenclosedenvironmentcanrangefromlaminartotransi-
tionaltoturbulentflowsandsometimesacombinationoftheseregimes,especiallyunder
transientconditions.Thecomplicatednatureofindoorairflowposesasignificantchal-
lengeforexperimentalstudies,astheyareusuallycumbersomeandcostly.However,with
therapidadvancementsincomputercapacityandspeed,CFDhasemergedasapowerful
alternativeforpredictingairflowsinenclosedenvironments[38].Bysolvingtheconser-
vationequationsformass,momentum,energy,andspeciesconcentrations,CFDcanpro-
videquantitativecalculationsforvariousairdistributionparameterswithinanenclosed
space.
Figure5.Typicalflowcharacteristicswithinanenclosedenvironmentwithdiverseflowmecha-
nisms.
8.CommercialSoftwareandOpen-SourceCFDCodes
Advancementsincomputerhardware,numericalmethods,andsoftwaredevelop-
menthavecontributedtotheenhancedcapabilitiesofCFDcodes.Numerouscommercial
softwareandopen-sourceCFDcodesareavailable,eachwiththeirstrengthsandspecial-
izations.Forexample,Ansys-Fluent,withitsuser-friendlyinterfaceandrobustpre-and
post-processingcapabilities,isidealforcomplexindustrialsimulations.Itoffersacom-
prehensivelibraryofturbulencemodelsandmultiphysicsfunctions.Intheliterature,
manyresearchershavesuccessfullyemployedthissoftwaretomodelenvironmentalcon-
ditionsinpoultryhouses[40–43].Itsexcellentdesigncapabilitiesmakeitsuitableforsolv-
ingcomprehensiveinterdisciplinaryproblems.Star-CCM+ismoreefficientandconven-
ientthangeneralCFDsoftwarebecauseitperformsresultprocessingwithoutseparate
Figure 5. Typical flow characteristics within an enclosed environment with diverse flow mechanisms.
The flow regime within an enclosed environment can range from laminar to transi-
tional to turbulent flows and sometimes a combination of these regimes, especially under
transient conditions. The complicated nature of indoor air flow poses a significant challenge
for experimental studies, as they are usually cumbersome and costly. However, with the
rapid advancements in computer capacity and speed, CFD has emerged as a powerful
alternative for predicting airflows in enclosed environments [
38
]. By solving the conserva-
tion equations for mass, momentum, energy, and species concentrations, CFD can provide
quantitative calculations for various air distribution parameters within an enclosed space.
8. Commercial Software and Open-Source CFD Codes
Advancements in computer hardware, numerical methods, and software develop-
ment have contributed to the enhanced capabilities of CFD codes. Numerous commercial
software and open-source CFD codes are available, each with their strengths and special-
izations. For example, Ansys-Fluent, with its user-friendly interface and robust pre- and
post-processing capabilities, is ideal for complex industrial simulations. It offers a compre-
hensive library of turbulence models and multiphysics functions. In the literature, many
researchers have successfully employed this software to model environmental conditions
in poultry houses [
40
–
43
]. Its excellent design capabilities make it suitable for solving
comprehensive interdisciplinary problems. Star-CCM+ is more efficient and convenient
than general CFD software because it performs result processing without separate post-
processing [
44
]. Phoenics proves valuable in process engineering simulations, especially
in modeling fluid flow and heat transfer in applications, such as airflow in buildings
and HVAC systems [
45
–
47
], allowing steady-state and transient simulations. Acusolve
efficiently handles large and complex simulations with parallel processing capabilities
and various turbulence models to simulate turbulent flows accurately [
48
,
49
]. PAM-Flow,
known for its robust capabilities, is ideal for simulating external aerodynamics, under-hood
flows, and thermal management of vehicles [
50
]. The main commercial CFD software is
listed in Table 1. In addition, OpenFOAM, SU2, Gerris Flow Solver, Code_Saturne, and
Elmer are the most widely used open-source CFD codes for the simulation of flows and
related phenomena.
Animals 2024,14, 501 8 of 21
Table 1. Some commercial CFD software.
Software Company Website (accessed on 22 May 2023)
Ansys-Fluent Ansys, Inc. (Canonsburg, PA, USA) https://www.ansys.com
Star-CCM+ Siemens (Plano, TX, USA) https://plm.sw.siemens.com
Comsol-CFD Comsol (Burlington, MA, USA) https://www.comsol.com
Phoenics Cham (London, UK) https://www.cham.co.uk
Flow Simulation Solidworks (Waltham, MA, USA) https://www.solidworks.com
Acusolve Altair (Troy, MI, USA) https://www.altair.com.es
CFD++ Metacomp Technologies, Inc. (Westlake Village, CA, USA) https://www.metacomptech.com
PAM-Flow Pacific Engineering Systems (Sydney, NSW, Australia) https://www.esi.com.au
Flow-3D Flow Science, Inc. (Santa Fe, NM, USA) https://www.flow3d.com
9. Case Studies and Applications
CFD is a powerful simulation tool that uses computers and applied mathematics to
model flow situations, heat, mass, and momentum transfer. Its applications in optimizing
the design and performance of agricultural buildings are precious. However, the scope
of this review is limited to studies explicitly examining the use of CFD to determine the
microclimate in poultry houses. The indoor climate in poultry houses is critical to animal
well-being and productivity. Air temperature, relative humidity, pollutant concentration,
and air movement significantly impact the birds’ ability to regulate their body temperature
and maintain homoiotherm. Therefore, understanding and controlling these parameters
are critical to creating optimal conditions for poultry production [16].
CFD can be applied to study and analyze various aspects of poultry house ventilation
and air quality under the following five main headings: inlet and fan configuration, ven-
tilation system design, air temperature–humidity distribution, airflow distribution, and
particle matter and gas emission.
9.1. Inlet and Fan Configuration
Improving climate control for poultry houses depends primarily on accurately control-
ling the ventilation rates throughout the facility. Although suitable equipment is available,
its use in most houses is limited. Another significant challenge is the uneven distribution
of airflow within the building. The airflow pattern within the poultry house serves as the
crucial connection between the incoming air and the microenvironment surrounding the
birds. Therefore, accurately controlling the airflow pattern is a priority [51].
The airflow patterns within a poultry house are greatly influenced by the building’s
geometry and the positioning of fans and inlets [
52
–
54
]. Using CFD, Cheng et al. [
26
]
explored the effect of inlet position and flap on airflow and temperature in a laying hen
house. The ventilation volume employed in the simulation corresponded to that observed
during the field trial, amounting to 229 m
3
s
−1
. The boundary conditions replicated those
of the validated model, with the exception of the AOZ, which was simplified using the
porous media approach. Accordingly, the heat generation rate within the AOZ was set
at
456.67 W m−3
. The findings revealed that the positioning of the inlet and the presence
of a flap had a significant impact on airflow and temperature near the inlet. Increasing
the inlet area in the gable wall and establishing a greater distance between the cages
and sidewall inlets led to higher airspeed, lower temperatures, and improved airflow
distribution. However, the study does have limitations. For instance, it did not explore how
humidity in the laying hen house varies with different inlet positions. Additionally, the
thickness of the evaporative pad might impact inlet air velocity, and the angles of the flaps
could change with varying inlet air velocity, affecting the reach of the inlet airflow to the
center of the ceiling. It is crucial to note that this study exclusively focused on laying hen
houses, and its findings may not be directly applicable to other poultry housing systems.
Tong et al. [
55
] conducted a study investigating the influence of different opening
percentages of air inlets on the airflow pattern. In their CFD study, the air inlets were
simulated as pressure inlets, where the incoming air was determined by the static differen-
Animals 2024,14, 501 9 of 21
tial pressure between the interior and the atmosphere. Considering that air inlets can be
variably opened from 0% to 100% in practical scenarios, the inlet structure within the com-
putational domain was configured to include different opening percentages, namely, 25%,
37.5%, 50%, 62.5%, 75%, and 100%. The researchers noted that the air velocity distributions
exhibited reduced magnitudes and less variability during autumn and winter compared to
the summer scenario. These differences were linked to decreased house ventilation rates
and the partially opened baffle inlets. Specifically, during autumn and winter, the baffle
inlets were opened at smaller angles, forming vortex airflow patterns due to high-velocity
air streams near the inlet.
In a study investigating the effects of fresh air vents on poultry house aerodynamics,
Trokhaniak et al. [
56
] proposed several recommendations. Firstly, they suggested the
installation of spoilers positioned above the fresh air valves at an angle of 75
◦
from the
vertical line. Additionally, they recommended that the exterior walls be attached to the
inside of a concrete frame. Furthermore, they proposed expanding the width of the poultry
house to a maximum of 22.36 m. Finally, they advised reducing the height of the flooring
to approximately 3.9 m above the floor level.
Du et al. [
57
] conducted a study to optimize the air inlet configurations using the CFD
model. For this study, a 3D CFD model was constructed to replicate the real dimensions of
a laying hen house, and its accuracy was validated by comparing the simulation results
with field measurements at specific positions. Given the inherent complexity of numerical
simulation of a 3D real-world scenario, certain approximations were unavoidable. Rec-
ognizing that it is impractical to model each bird within the geometric representation,
the researchers employed a porous media model to simulate the AOZ, ignoring specific
details related to the feeding and water supply systems. The CFD results revealed that
the positioning of all the air inlets on the side walls of the building resulted in significant
vorticity at the front, suggesting uneven air movement within the facility. However, when
the air inlets were relocated to the front wall, a more uniform flow pattern with reduced
vorticity was achieved. In addition, the researchers used CFD simulations to investigate the
effects of correctly sized air inlets installed in the center of the side walls. They found that
this configuration could effectively decrease the expected high temperatures at the end of
the building without the need to increase the ventilation rate or consume additional energy.
Kucuktopcu and Cemek [
58
] applied the CFD technique to enhance their comprehen-
sion of indoor conditions in poultry houses, offering valuable insights for producers and
end-users to improve management decisions. The simulation results made it clear that
there are stagnant areas opposite the fans within a broiler house. To address this issue,
they recommended a corrective measure of shutting off inlets closer to the fan region and
opening inlets further away from the fans. By doing so, they explained that the high static
pressure created in this region would facilitate better air mixing and alleviate the presence
of stagnant areas. This adjustment was proposed to enhance the air circulation and create
more favorable conditions for the poultry house environment.
Zou et al. [
59
] examined the impact of installing windshields on the airflow distribution
in poultry houses during summer. By analyzing CFD simulation results, the researchers
determined the optimal installation height for the windshield. The findings revealed that
applying windshields led to a notable increase in wind speed and reduced temperature
inside the house. The numerical simulations also showed that the appropriate installation
height should be 1.8 m.
9.2. Ventilation System Design
Ventilation systems are essential in poultry production to control environmental
conditions, and their design is also of paramount importance, as the airflow patterns in the
house determine the characteristics and uniformity of environmental parameters.
Guerra Galdo et al. [
60
] conducted a CFD simulation study to analyze and compare
three poultry house designs: tunnel, semi-tunnel, and improved semi-tunnel. These
designs featured different configurations of inlets and fans. The study implemented a
Animals 2024,14, 501 10 of 21
2D steady-state model assuming constant density and second-order flow. The model
considered the production of sensible heat, which was estimated for 5-week-old animals
with a body weight of 2.5 kg. Heat production was included in the model as a uniform
flux of sensible heat (101.94 W m
−2
) from the concrete floor. The CFD simulation results
revealed that the improved semi-tunnel configuration performed better than the tunnel and
semi-tunnel designs.
Seo et al. [
61
] developed and modeled four modified ventilation systems (a chimney, a
side vent, a pipe under the roof, and a side-up vent at the eaves) for a naturally ventilated
broiler house. The CFD models were created based on heat production of 110.5 W m
−2
,
considering the entire floor area occupied by broilers. The outside air temperature was set
at 0.6
◦
C, while the inside was assumed to be 25
◦
C. The CFD simulation results indicated
that, unlike the conventionally controlled model, the upgraded model was governed by
an on–off timer responsive to the inside temperature, reducing dependence on arbitrary
atmospheric conditions. Furthermore, among the configurations tested, it was observed
that the model with a diffuser under the chimney inlet exhibited the best performance.
The tunnel ventilation system is widely used to control the indoor environment in
poultry houses. However, maintaining an optimum indoor temperature in winter proves
to be challenging. This difficulty in regulating the temperature can lead to cold stress in the
chickens and affect their production performance. To solve this problem, Yang et al. [
62
]
introduced an innovative double-duct ventilation system that combines the benefits of
an exhaust air heat recovery system and a perforated duct ventilation system using CFD
techniques. The novel double-duct ventilation system comprises multiple units evenly
distributed along the side walls, each of which can be controlled independently for precise
environmental management. These ventilation devices consist of an inner duct, outer duct,
fresh air fan, and exhaust air fan. The total ventilation rate for the novel double-duct system
was set at 65,300 m
3
, which is consistent with the tunnel ventilation system installed in the
poultry building. For the numerical analysis, the complexity was reduced by simplifying
each tier of cages to one resistance unit. To simulate the resistance effect of the chickens
and cages on the airflow, the loss coefficients along three directions were set as 1.2 m
−1
,
and the porosity was set as 0.85 in the resistance unit. The heat production of the chickens
was assumed to be 4.1 W kg
−1
. The authors emphasized that the innovative double-duct
ventilation system proves to be extremely effective in preheating cold fresh air, preventing
cold stress in chickens, and creating a favorable thermal environment. Compared to the
conventional tunnel ventilation system, the novel double-duct ventilation system resulted
in a significant increase in the average indoor temperature of the poultry house, with a
significant increase of 4.4 ◦C.
In a study conducted by Babadi et al. [
63
], the authors focused on developing an
effective ventilation system by addressing the limitations identified in the models proposed
by Wang and Wang [
64
]. Three new models were introduced, each of which was simulated
by adjusting the dimensions of the evaporative cooling pads and changing the number
and position of the exhaust fans. The evaluation showed that the second new model, with
fifteen fans on the east wall and three evaporative cooling pads on the west wall, performed
the best.
Tong et al. [
42
] introduced the upward airflow displacement ventilation (UADV)
system, a novel ventilation system. To assess the performance of the UADV system, the
researchers compared it with a typical tunnel ventilation (TV) system using the CFD tech-
nique. The study findings demonstrated that the UADV system exhibited 46–129% higher
air exchange effectiveness within the cages than the TV system. This study contributes to
our comprehension of ventilation system design, yet additional research is crucial for the
practical implementation of the UADV system in commercial layer houses. Further studies
are required to delve into specific design considerations for air inlet ducts and the ceiling,
ensuring practical and effective application in real-world production environments.
Another study by Bustamante et al. [
65
] utilized CFD to investigate the efficiency
of ventilation systems and identify optimal designs for poultry houses. Their findings
Animals 2024,14, 501 11 of 21
revealed that mechanical cross-ventilation systems, although suitable for common weather
conditions, may not be sufficient in preventing mortality episodes caused by heat stress.
This is attributed to the fact that these systems provide lower air velocity values than
what animals require under such challenging conditions. The authors emphasized the
importance of future instrumentation efforts and specifically advocated the development
of multi-sensor systems capable of providing isotemporal measurements of air velocity
components. They also stressed the importance of considering animal thermal comfort
in research focused on characterizing buildings and identifying key elements for optimal
poultry farms.
9.3. Airflow Distribution
Poultry houses with inadequate ventilation systems are prone to high mortality rates,
especially when the microenvironment around the birds becomes hot, humid, and stag-
nant. It is crucial to maintain uniform air velocity within the bird-occupied zone to deter
their migration toward better-ventilated but already crowded areas, as this behavior can
ultimately result in a higher mortality rate among the birds.
Cheng et al. [
66
] conducted a study to address the issue of reduced air speed in the
AOZ during summer tunnel ventilation in a hen house. Typically, a large free space beneath
the ceiling is designed to fully mix the cold inlet air with room air during winter. However,
this design is not optimal for tunnel ventilation, as a significant portion of the ventilation
air passes through the free space under the ceiling instead of the AOZ. To overcome this
problem, the researchers investigated the application of deflectors beneath the ceiling CFD
simulations. Deflectors were introduced to redirect the airflow toward the AOZ, thereby
increasing air speed and the wind chill effect. The study analyzed the effects of different
heights and intervals of the deflectors along the length direction of the cage. The findings
revealed that the variation trends of airspeed were nearly identical under different heights
of deflectors, indicating that height variation had minimal impact on airflow distribution.
However, significant differences in airspeed variation trends were observed under varied
intervals of the deflectors. This suggested that the spacing between the deflectors played
a crucial role in determining the airflow distribution and air speed within the AOZ. The
study also found that the uniformity of air speed distribution was positively related to the
height of the deflectors and negatively related to the interval between them. This means
that higher deflectors and closer spacing between them contributed to a more uniform air
speed distribution within the AOZ.
In a study conducted by Blanes-Vidal et al. [
67
], a comprehensive assessment of
ventilation system designs was performed to evaluate the effectiveness of these designs
in generating suitable air velocities within the AOZ. The authors performed four CFD
simulations to analyze the airflows in a mechanically ventilated commercial poultry house.
The accuracy of these simulations was verified by comparing the simulated and measured
air velocities. In scenario 1, the inlet velocity was assumed to be uniformly distributed
across all inlet areas. In scenario 2, the air velocity at each inlet was equated to the
time-averaged mean velocity measured at each specific inlet using a portable hot wire
anemometer. In scenario 3, the atmospheric pressure was used as the boundary condition at
the inlets, while the air velocity was fixed at the outlets. Finally, in scenario 4, the boundary
conditions ‘velocity at the inlets’ and ‘negative relative pressure at the outlets’ were used.
The findings indicated that refining CFD results by including at least 15 indoor air velocity
measurements led to a more accurate estimate of the mean air velocity at the height of the
birds. The authors, therefore, concluded that the study could provide valuable insights into
the actual airflow dynamics in commercial poultry houses. However, they also pointed
out the practical challenges encountered in measuring and modeling real poultry houses
during the study.
Chen et al. [
41
] employed CFD modeling techniques to quantify the efficiency of
ventilation systems in maintaining optimal and consistent living conditions, particularly
at the level of individual hens. A noteworthy aspect of the study was the introduction
Animals 2024,14, 501 12 of 21
of a comprehensive CFD model that included individual hen models. This approach
significantly enhanced the robustness of their assessment of the birds’ welfare conditions.
However, the authors pointed out that various factors, including the relative location of
inlets and exhaust fans and the dimensions of baffles, play a crucial role in shaping the
indoor environment. Therefore, they suggested that further CFD analysis could investigate
the uniformity of temperature and air velocities together with environmental parameters at
the individual hen level to address practical issues, such as floor eggs.
9.4. Air Temperature–Humidity Distribution
Hot and humid conditions in poultry houses adversely affect bird welfare and produc-
tivity [
52
,
68
]. As temperatures and humidity rise, heat stress becomes a problem, resulting
in reduced feed intake, lower meat/egg production, and increased mortality [
69
]. To over-
come these challenges, it is critical to implement sustainable ventilation designs that can
maintain an optimal thermal environment for poultry. However, relying only on maximum
ventilation may not be sufficient in certain hot weather conditions, requiring evaporative
fan–pad cooling systems [
70
,
71
]. During the summer, the prevailing ventilation practice
involves operating an evaporative cooling system and installing cooling pads on the gable
wall and/or both sidewalls at one end of the building while fans are placed at the opposite
end [72].
The CFD study by Küçüktopcu et al. [
36
] demonstrated the potential benefits of imple-
menting evaporative fan–pad cooling systems in summer. Implementing an evaporative
cooling pad system during the summer effectively mitigated high temperatures. When
the mean air temperature inside the house exceeded 25
◦
C, this system resulted in an
approximate decrease of 3
◦
C. Notably, in areas near the pads where air temperatures were
low (22.16–22.88
◦
C), there was a gradual increase of almost 2.50
◦
C from the pads to the
exhaust fans.
In other studies, Al Assaad et al. [
73
] conducted a comparative analysis of the ef-
fectiveness of three passive cooling systems in meeting thermal comfort and indoor air
quality standards within a poultry house situated in a semiarid climate. The first two
systems under investigation were a direct evaporative cooler and a crossflow dew point
evaporative cooler. These systems deliver air through conventional tunnel ventilation to
ensure uniform thermal conditions and indoor air quality. The third system introduced
a dewpoint evaporative cooler and paired it with a localized ventilation system, aiming
to achieve additional reductions in air and water consumption while maintaining desired
environmental conditions in the poultry house. The research findings revealed that the
dewpoint evaporative cooler performed better than the direct evaporative cooling system.
Wang and Wang [
64
] employed CFD techniques to comprehensively analyze the
environmental conditions in a mechanically ventilated commercial layer house equipped
with a wet pad cooling system. In the simulation of the original house, two improved
cases were created to improve the indoor environmental conditions. In improved
case 1
,
two pads
originally installed in the side walls were removed. In improved case 2, five
exhaust fans were installed on each end wall with a distance of 1.9 m between the fans,
and two wet pads were placed in the center of each side wall. The simulations showed
that of the three cases, improved case 2 proved to be the optimal choice, as it created
an environment with reduced opportunities for layers to experience severe heat stress
conditions, attributed to the younger age of the air. The main limitation of this study is that
it does not take into account relative humidity, which is a crucial factor for the performance
and production of laying hens.
The distribution of environmental variables and thermal comfort provided a more
comprehensive understanding of ventilation and thermal conditions in the poultry house
and provided insights to improve facility design and management to enhance poultry
welfare [
74
–
76
]. In a specific study focused on thermal comfort issues, Tong et al. [
55
]
employed a 3D CFD model to assess the temperature–humidity index (THI) and heat stress
levels during summer, autumn, and winter. The study findings revealed that heat stress
Animals 2024,14, 501 13 of 21
was prevalent in 69.1%, 78.0%, and 18.4% of cages during summer, autumn, and winter,
respectively, as determined by the THI. Furthermore, 18.3% of the cages experienced cold
stress during winter due to low incoming air temperature and insufficient air mixing.
9.5. Particle Matter and Gas Emission
Particulate matter (PM) and gas emissions constitute a significant air pollution concern
for commercial poultry production facilities [77].
Knight et al. [
78
] developed a comprehensive COMSOL software model to simulate
the poultry PM collection process in an electrostatic precipitator (ESP) module. The model
offered a cost-effective alternative to physical prototypes for assessing ESP designs aimed
at mitigating PM in poultry facilities. Pawar et al. [
79
] investigated the PM and gaseous
contaminant levels in laying hen houses under different ventilation scenarios.
Some studies have analyzed the spatial distribution of NH
3
concentration in poultry
houses [
80
,
81
]. Gonçalves et al. [
17
] developed a numerical model to accurately forecast the
velocity fields within the domain and estimate the dispersion of NH
3
emissions from the
poultry litter in the housing. Six different situations were simulated to replicate summer,
winter, and mid-season periods, including the day and night periods. The findings revealed
that in winter and summer configurations, characterized by lower extraction flow rates,
there was a considerable increase in NH
3
concentration along the tunnel, with inefficient
removal of NH
3
. Conversely, in situations with higher air extraction flow rates (mid-season),
NH
3
was effectively removed, leading to consistently low concentrations throughout
the tunnel.
10. Practical Challenges in Implementing CFD in Poultry Production
CFD is a valuable tool for analyzing airflow and ventilation in poultry buildings. It
also provides insights into the distribution of pollutants, thermal conditions, and potential
areas of improvement for bird health and performance. However, it does have certain
limitations and challenges. In this section, we present some limitations and solutions on
the application of CFD, which should be addressed in future research.
10.1. Data Acquisition and Validation
Data acquisition involves collecting relevant information to monitor and control the
poultry production environment. In the context of CFD, data acquisition primarily focuses
on gathering data related to environmental parameters, including temperature, humidity,
air velocity, gas concentrations (e.g., CO
2
, NH
3
), and particulate matter levels in the
poultry house.
To achieve effective data acquisition in poultry production, sensor systems must be
strategically placed throughout the facility [
36
]. These sensors continuously gather real-
time data, which is then transmitted to a central control system or cloud-based platform.
Advanced sensor technology and Internet of Things (IoT) devices have made collecting
and managing this data easier, providing poultry farmers with a comprehensive view of
their operation [82].
Validation is critical in ensuring simulated CFD models accurately reflect real-world
poultry production conditions. A CFD model that is not compared with measurements
would not be credible and, consequently, could not be used as a relevant tool to test the
system’s response under different operating conditions [
83
]. Validation involves comparing
CFD predictions with actual measurements collected by sensors in the poultry house [
65
,
67
].
Nevertheless, obtaining accurate and practical results for fluid dynamic factors through
field experiments is inherently challenging. This challenge arises from the inherent vari-
ability and instability of field conditions, which require significant investment in time and
labor. Therefore, some research teams have explored alternative approaches to optimize
their experimental conditions. These approaches include wind tunnel tests, Particle Image
Velocimetry (PIV) tests, scale model simulations, and similar methods [
84
,
85
]. Additionally,
Animals 2024,14, 501 14 of 21
some researchers have turned to pre-existing data generated by previous investigators with
similar research objectives to validate their CFD models [63].
10.2. Computational Resource Requirements
Simulations can be computationally demanding and require significant computational
resources and time [
86
,
87
]. Handling large-scale simulations for entire poultry buildings
with multiple scenarios can pose computational power and storage capacity challenges. The
computational demands of CFD simulations arise from the need to solve complex equations
that describe the behavior of fluids and their interactions with solid surfaces. These
simulations involve dividing the domain into a grid or mesh of small computational cells
and solving the governing equations for each cell. As the domain size and the simulations’
complexity increase, the number of cells and the computational time required also increase.
However, advancements in computing technologies and optimization techniques continue
to improve the efficiency and accessibility of CFD simulations.
10.3. Simplification and Validity of Assumptions
In small-scale animal barns with relatively few animals, it is feasible to include detailed
models of individual animals in CFD simulations [
88
]. However, for larger barns and a
higher number of animals, the computational requirements become more demanding, and
the inclusion of detailed animal models becomes impractical. Therefore, the presence of
animals has often been neglected in several studies, as large-scale simulations with high
mesh numbers present computational challenges [
65
,
67
]. The limited computational power
of ordinary desktops or professional workstation computers may not be sufficient to handle
such simulations [89].
To simplify the geometric modeling of the AOZ, researchers have turned to porous
media models in CFD simulations of barns. These models represent animal blocks and/or
slatted floors as porous regions, allowing for more computationally intensive simula-
tions [
90
,
91
]. Porous media models provide an effective trade-off between computational
efficiency and capturing the effects of animals on airflow and ventilation within the barn.
Applying the porous media assumption in CFD simulations of a poultry house simpli-
fies the complicated geometry of the AOZ to a porous region. The idea of porous media is
to insert a source term in Navier–Stokes equations. The source term consists of two parts:
the viscous loss term (Darcy’s law) and the inertial loss term (Equation (4)).
∆Pi
∆χi
=− 3
∑
j=1
Dij µνj+
3
∑
j=1
Cij
1
2ρ|ν|νj!(4)
where
∆Pi/∆χi
: the pressure drop per unit length for the ith (x, y, or z) direction (Pa m
−1
),
µ
: the dynamic viscosity of air (Ns m
−1
),
νj
: the inlet air velocity in x, y, or z directions
(m s
−1
), D: the matrix of viscous resistance coefficients (m
−2
), C: the matrix of inertial
resistance coefficients (m
−1
),
ρ
: the air density (kg m
−3
), and
|ν|
: the magnitude of the
velocity (m s−1).
Resistance coefficients are employed to capture the relations between inlet velocities
and flow resistance within the AOZ. These coefficients are usually determined by empirical
correlations or experimental measurements. Performing CFD calculations to evaluate
pressure drops across the AOZ involving discretely modeled birds and varying inlet
velocities provides a practical way to derive the resistance coefficients. This approach
allows for a simulation of the flow behavior and pressure drops within the bird zone under
various operating conditions [92].
Some studies have confirmed the feasibility of applying porous media in poultry
houses in some cases. For example, Du et al. [
57
] demonstrated the successful application
of porous media models in studying airflow distributions, temperature, and relative hu-
midity in a poultry house. By simplifying the AOZ as a porous media, the researchers
could simulate the airflow patterns and environmental conditions within the poultry house.
Animals 2024,14, 501 15 of 21
Cheng et al. [
92
] examined how the geometry, arrangement, and weight of birds inside
cages impacted the flow resistance experienced by laying hens. They calculated resistance
coefficients by modeling the area around the birds as a porous medium in various scenarios
using CFD techniques. The simulation results revealed a significant impact of hen distri-
bution on flow resistance. The variation in flow resistance was attributed to the positive
correlation of the drag force with the projected area. Different distributions could signifi-
cantly influence the projected area perpendicular to the flow directions. This alteration in
the projected area could lead to increased drag force and thus increased momentum loss.
Consequently, air velocity and flow resistance in the AOZ could be affected. Also, body
weight had a significant effect on flow resistance, and flow resistance had a lesser variation
with increased body weight.
10.4. Selection of a Proper Turbulence Model
Selecting an appropriate turbulence model is crucial in developing CFD simulations.
Turbulence models are necessary to provide closure for the Navier–Stokes equations, which
describe fluid flow behavior. The challenge with turbulence modeling is that no single
model can accurately represent all Reynolds flow regimes. Reynolds flow regimes refer
to the range of flow conditions characterized by the Reynolds number, which determines
the relative importance of inertial forces to viscous forces in the flow. Different turbulence
models are designed to capture specific turbulence characteristics under certain flow
conditions [39,93].
The choice of a turbulence model depends on several factors, including the specific
flow conditions, available computational resources, and desired accuracy. It often involves
a trade-off between accuracy and computational cost. It is common practice to validate
turbulence models against experimental data or higher-fidelity simulations to assess their
performance for a particular application.
In the field of CFD, numerous turbulence models have been proposed in the literature.
Choosing an appropriate model is crucial for predicting the indoor environment of poultry
buildings. A review of CFD applications in poultry buildings revealed that the most
commonly used turbulence models were the standard k-
ε
, renormalization group (RNG)
k-ε, and realizable k-εmodels (Table 2).
Table 2. Summary of published research on the most used k-εturbulence models.
Reference
Turbulence Model
Validation Remarks
Blanes-Vidal et al. [67] Standard k-εAir velocity
The inclusion of a minimum of 15 indoor air velocity
measurements significantly enhanced the results of CFD
analysis, resulting in a significantly improved estimation of
the average air velocity at bird height.
Seo et al. [61] RNG k-εAir temperature,
air velocity
To assess the local and overall ventilation efficiency of six
broiler houses, which consisted of one conventional house
and five improved houses, a comprehensive analysis was
conducted utilizing CFD technology.
Bustamante et al. [65] Standard k-εAir velocity
To analyze a cross-mechanical ventilation system and assess
the air velocity distribution, two methodologies were
employed: CFD simulations and direct measurements.
Cheng et al. [66] Standard k-εAir temperature,
air velocity
The application of deflectors beneath the ceiling was
investigated using CFD simulations.
Tong et al. [55] RNG k-ε
Air temperature,
air velocity, and
humidity
A 3D CFD model was created to simulate various
parameters, including air velocity, air temperature, humidity,
and heat stress indices, within a commercial layer house.
Animals 2024,14, 501 16 of 21
Table 2. Cont.
Reference
Turbulence Model
Validation Remarks
Du et al. [57] Realizable k-ε
Air temperature,
air velocity, and
humidity
To ensure accuracy, a 3D CFD model was constructed based
on the actual dimensions of a laying hen house. The
accuracy and reliability of the model were verified by
comparing the simulation outcomes with field
measurements obtained at 30 distinct locations within
the facility.
Cheng et al. [26] Standard k-εAir temperature,
air velocity
The influence of inlet position and flap configuration on
airflow and temperature within a laying hen house was
meticulously examined through CFD simulations.
Chen et al. [41] Standard k-εAir temperature,
air velocity
An investigation was conducted to explore alternative
ventilation schemes to establish a suitable design for
ventilation systems in cage-free hen houses.
Yang et al. [62] RNG k-εAir temperature,
air velocity
A novel double-duct ventilation system was introduced by
merging the benefits of an exhaust air heat recovery system
with a perforated duct ventilation system. This innovative
approach aimed to harness the advantages of both systems
for improved ventilation and energy efficiency.
Küçüktopcu et al. [36] RNG k-ε
Air temperature,
air velocity, and
humidity
The CFD technique was employed to model the spatial
variabilities of the microclimate within a mechanically
ventilated broiler house during both summer and
winter seasons.
Unfortunately, a lack of comprehensive research has thoroughly examined the im-
pact of different turbulence models on the accuracy of predictions regarding the indoor
environment of poultry houses. To address this gap, Kucuktopcu and Cemek [
40
] focused
on evaluating the performance of three different variants of the k-
ε
turbulence model:
the standard k-
ε
, RNG k-
ε
, and realizable k-
ε
. The objective was to determine which
model provided the most accurate simulation of the internal turbulent flow in a poultry
house. Their findings indicated that the RNG k-
ε
turbulence model agreed best with the
measurements of airspeed and temperature. Therefore, its use and typical parameters were
recommended for simulating the indoor environment of poultry houses.
11. Future Research Directions
11.1. Hybrid CFD and Machine Learning (ML) Approaches
Hybrid approaches combining CFD and ML techniques have gained significant at-
tention recently, especially in fluid dynamics and engineering [
94
,
95
]. These approaches
leverage the strengths of both CFD and ML to enhance the accuracy, efficiency, and robust-
ness of simulations and extract valuable insights from complex fluid flow problems [
96
,
97
].
ML algorithms can be used to generate training data for CFD simulations. This can
help reduce the computational cost of running CFD simulations, especially for problems
with high-dimensional parameter spaces. Also, ML algorithms can improve turbulence
modeling in CFD simulations. They can learn from experimental data or high-fidelity
simulations to better capture complex turbulent flows, reducing the reliance on traditional
turbulence models. The hybrid method has proven valuable in tackling the computational
challenges associated with CFD models for fluid flow. This method has yielded promising
results, effectively balancing accuracy with computational efficiency [98,99].
11.2. Coupling CFD with Building Information Modeling (BIM)
Coupling CFD with BIM is a forward-looking approach that can enhance buildings’
design, energy efficiency, and overall performance [
100
]. BIM-CFD integration facilitates
early-stage analysis during the design phase and optimizes airflow and temperature distri-
bution [
101
]. This can lead to energy savings, reduced HVAC system sizes, and improved
Animals 2024,14, 501 17 of 21
thermal comfort. As technology continues to advance, this integration is likely to play an
increasingly essential role in the construction and operation of buildings in the future.
11.3. Real-Time CFD Simulations and Feedback Control Systems
Real-time CFD simulations and feedback control systems can be integrated to cre-
ate closed-loop control systems. In such systems, CFD simulations provide real-time
data about the fluid flow, which are then used as feedback to adjust control parameters
in an automated or semi-automated manner. This integration offers significant advan-
tages in process optimization, efficiency improvement, and safety in a wide range of
industries [102–105]
. These technologies continue to evolve as computational capabilities
and control strategies advance.
12. Conclusions
This paper comprehensively reviews the latest advancements in CFD modeling tech-
niques for assessing environmental conditions in poultry houses and extensively covers
the practical challenges associated with implementing CFD in different poultry production
settings. From this review paper, the following conclusions can be made.
Careful validation of CFD results is crucial to ensure their accuracy and predictive
capability. The integration of CFD simulations with experimental research provides a
comprehensive insight into the climatic conditions in poultry houses. The use of CFD
simulations can be particularly valuable in the initial stages of poultry house design, as it
allows for the exploration of potential alternatives and design improvements.
Modeling the exact position and size of the birds is essential to achieve the most
accurate solutions. This approach is particularly important as the interior of the house is
inhomogeneous and there is an inherent resistance to airflow at the level of the birds. In
cases with complex geometries and poultry houses with a higher number of birds, it is
advisable to simplify the geometric modeling of the AOZ using a porous media model and
introduce a uniform heat flux into the CFD model.
The overview of CFD applications in poultry houses shows that the most commonly
used turbulence models are the standard k-
ε
, RNG k-
ε
, and realizable k-
ε
models. However,
it is noted that there is a lack of comprehensive research that thoroughly investigates the
effects of the different turbulence models on the accuracy of predictions for the indoor
environment of poultry houses. It is, therefore, recommended that detailed studies be
conducted on this topic.
In future studies, the integration of ML, BIM, and feedback control systems with
CFD promises to improve the analysis of the indoor environment in poultry houses. This
comprehensive approach can contribute to higher efficiency, informed decision-making,
and better environmental conditions for poultry houses.
Author Contributions: Conceptualization, E.K. and B.C.; methodology, E.K. and H.S.; investi-
gation, E.K. and B.C.; resources, E.K., B.C. and H.S.; writing—original draft preparation, E.K.;
writing—review
and editing, E.K., B.C. and H.S.; visualization, E.K. and H.S.; supervision, B.C. and
H.S. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: No new data were created or analyzed in this study. Data sharing is
not applicable to this article.
Conflicts of Interest: The authors declare no conflicts of interest.
Animals 2024,14, 501 18 of 21
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