Performance and Efficiency Improvement of an Axial Flow Fan by

Combining the FANDAS and the PIAnO Codes

Chan Lee

1,a

, Hyun Taek Byun

2,b

, Sang Yeol Lee and Sang Ho Yang

3,c

Department of Mechanical Engineering, University of Suwon, 17 Wauangil, Hwaseong, Republic of Korea

Kyungwon Tech., 81 Yatap-ro, Seongnam, Republic of Korea

Samwon E&B, 233 Jeongwangchun-ro, Shiheung, Republic of Korea

Keywords: Axial Flow Fan, CFD Simulation, Optimization, Performance Prediction.

Abstract: The present paper deals with the optimization study of a variable-pitch axial flow fan by combining fan design

method of the FANDAS (FAN Design and Analysis System) code and optimization algorithm of the PIAnO

(Process Integration, Automation and Optimization) code. The FANDAS code is used as fan design program

to design 3D fan rotor blade geometry and to predict designed fan's performance and efficiency, and it is also

used as simulation engine for fan design optimization problem. The PIAnO code is used as optimization

program to apply a function-based optimization algorithm to the FANDAS code and to find the optimal fan

design solution for efficiency maximization. In this optimization study, spanwise camber, stagger angles and

chord lengths of axial flow fan are selected as design variables and the design constraints are set to design

flow capacity, total pressure, power and blade angles, solidities. Through the design optimization by

combining the FANDAS and the PIAnO codes, optimal fan rotor blades are obtained and then they are

coupled with existing outlet guide vanes to construct the final fan stage. Computational fluid dynamics (CFD)

analyses are conducted to verify the performance and efficiency of the optimal fan design, and the CFD

calculation results are matched well with the FANDAS predictions for performance and efficiency of optimal

fan. The CFD results also show that the optimal fan design gives the efficiency improvement of about 6.7%

compared to the initial design. Furthermore, the FANDAS performance predictions of the optimal fan under

variable-pitch conditions show that the optimal fan can be operated with wide flow capacity range between

2000 and 5000 m

/min and high efficiency above 80 % by adjusting fan rotor blade pitch angle.

1 INTRODUCTION

Axial flow fans are key flow elements of various

ventilation, air conditioning and energy systems in

industrial, commercial and residential fields. Recent

technical issue of axial flow fan is to improve fan

performance and efficiency because worldwide

climate change and carbon neutral trends call for

more energy saving of all kinds of machines and

equipment. Since variable-pitch axial flow fans are

operated by setting fan blade setting angle

automatically for maintaining high efficiency over

wide flow capacity range, they have been being

developed by many fan industries and introduced in

fan application systems. In high-efficiency axial flow

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fan design, it is very critical for fan designer to

optimize 3-D fan blade geometry because air flow

motion on fan blade surface affects severely the

aerodynamic characteristics and efficiency of the fan.

For this reason, .many researches have applied

optimization techniques to design and optimize fan

blade geometry for high efficiency fan development

(Angelini, 2017; Edward, 2021).

Thus, in order to maximize fan efficiency, the

present paper proposes a new variable-pitch axial

flow fan design method coupled with optimization

algorithm. The optimal fan designed by the present

method is verified by using the CFD simulation and

its variable-pitch operation and performance

characteristics are predicted and examined.

346

Lee, C., Byun, H., Lee, S. and Yang, S.

Performance and Efﬁciency Improvement of an Axial Flow Fan by Combining the FANDAS and the PIAnO Codes.

DOI: 10.5220/0012098500003546

In Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2023), pages 346-351

ISBN: 978-989-758-668-2; ISSN: 2184-2841

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

2 FAN DESIGN AND

PERFORMANCE PREDICTION

The present study employs the FANDAS code for

designing 3D fan rotor blade geometry and predicting

the fan performance and efficiency. With the use of

the FANDAS code, fan blade sections are designed

from the camber, the stagger angles and the chord

length as design variables and then 3D fan blade

geometry is constructed by the stacking of blade section

elements along blade span height from hub to tip. The

camber line of blade section is determined by single

circular arc formula with given camber angle and

NACA 65 airfoil thickness distribution is added onto

the camber line to construct blade element profile

(refer to Figure 1).

Figure 1: Nomenclature for blade design parameters.

The FANDAS code can also predict the

performance, power and efficiency of designed fan by

using the through-flow analysis method of the

streamline curvature-computing scheme for the pitch-

averaged radial equilibrium equation of flow motion

with total pressure loss models (Novak, 1967).

𝑑𝑉





𝑑𝑟

𝐴



𝑟



𝑉





𝐵𝑟

(1)





2𝑠𝑖𝑛



𝛽

𝑠𝑖𝑛𝜙

𝑉



𝑑𝑉



𝑑𝑚



𝑐𝑜𝑠𝜙

𝑟





𝑐𝑠𝑐



𝛽



𝑄

𝑑𝑄

𝑑𝑟





𝑑



𝑐𝑜𝑡



𝛽



𝑑𝑟



𝑐𝑜𝑡



𝛽

𝑟



2Ω

𝑉



𝑐𝑜𝑡𝛽

(2)





2𝑠𝑖𝑛



𝛽

𝑄

𝑑



𝐼𝑄



𝑑𝑟





𝑟





𝑄

𝑑𝑄

𝑑𝑟



(3)

where 𝑉



,𝛽,𝑟



and ϕ represent meridional flow

velocity, relative flow angle, streamline curvature

radius and slope, and I,Ω and Q mean rothalpy,

angular rotational speed and entropy function.

The FANDAS code was developed and

commercialized by the authors and its details are

described in the reference.(Lee, 2021; Kyungwon

Tech. 2017).

The FANDAS code is applied for designs and

performance predictions of axial flow fans without or

with blade sweep. Three dimensional geometry of

axial flow fan blade rotor is designed by the

FANDAS code and depicted in Figure 2, and the fan

performance curves are also shown in Figure 3.

Comparing the performance prediction and the test

results of axial flow fan (Hurault, 2010), the

FANDAS code can be considered as reliable tool to

predict overall fan performance over entire flow

capacity range except at very low flow condition

causing stall or surging.



Figure 2: Fan blade rotor with 25 deg. Sweep.

Air flow capacity[CMM]

10 20 30 40 50 60

Static Pressure[mmAq]

: prediction( sweep = 0 deg )

: predcition( sweep = 25 deg )

: experiment( sweep = 0 deg )

: experiment( sweep = 25 deg )

Figure 3: Performance curves of swept fans.

The present study applies the FANDAS code in

the performance prediction of a variable pitch axial

Performance and Efﬁciency Improvement of an Axial Flow Fan by Combining the FANDAS and the PIAnO Codes

347

flow fan designed with camber and stagger angles of

fan blade section as free design variables to construct

3D fan rotor geometry. Figure 4 shows the spanwise

distributions of camber and setting angles (setting

angle = 90

– stagger angle) over blade span height.

Using the distributions of blade angles of Figure 4,

the present study designs and constructs twisted fan

rotor blades as shown in Figure 5. Figure 6 shows the

performance prediction results of a variable pitch

axial flow fan designed with the camber and the

stagger angles of Figure 4. As shown in Figure 6, the

FANDAS predictions are favorably matched with the

test results (van der Spuy, 1997) at different fan-

blade pitch conditions when the setting angle of blade

hub is set to 25, 35 or 45 deg.



Figure 4: Camber and setting angle distributions.



Figure 5: Rotor blades of a variable pitch fan.

The comparisons between the FANDAS

prediction and the measurement results imply that the

FANDAS code can be used as the design and

performance prediction tool of axial flow fan with

high prediction accuracy and then can be a suitable as

simulation engine of design optimization problem.

Figure 6: Performance curves of variable pitch fan.

3 THE PRESENT FAN DESIGN

OPTIMIZATION AND

VERIFICATION

The present study uses the FANDAS code as

simulation engine in constructing the design

optimization problem for efficiency (η) maximization

of axial flow fan. As shown in Figure 7, the FANDAS

code is incorporated with Hybrid Metaheuristic

Algorithm (HMA) of the PIAnO code (PIDOTEC,

2021) as optimization technique and some

mathematical formulations are made by using

camber and stagger angles as design variables (Kim,

2022. It is noted that the HMA combines two

different metaheuristic algorithms, differential

evolution (DE) and cuckoo search (CS), using bi-

population concepts.

In the presnt design optimization study, objective

function is defined as the total pressure efficiency of

fan, which is predcited by the FANDAS code, and

design variables are the camber angles ( 𝜃



), the

stagger angles (ξ) and the chord lengths (c) fan rotor

blade sections, so optimization problem is formulated

Optimize 𝜃







,ξ





and c





to maximize η

With constraints in Table 1

(4)

Here the camber and the stagger angles are defined as

design variables at five blade span locations, while

the chord lengths are defined as design variables at

the three locations of hub, mid-span and tip. For

smooth change of chord length along blade span, the

present study set the chord lengths at three locations

Blade span length[mm]

0 100 200 300 400

Camber and setting angles[deg.]

: Camber angle

: Setting angle

Flow capacity[CMS]

012345678

Fan static pressure[Pa]

100

150

200

250

300

350

400

450

500

: Prediction( 25 deg )

: Prediction( 35 deg )

: Prediction( 45 deg )

: Test( 25 deg )

: Test( 35 deg )

: Test( 45 deg )

SIMULTECH 2023 - 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

348

of hub, mid span, and tip, and, at the point between

which the blade angles are defined; the chord length

is obtained by parabolic interpolation of chord lengths

at the three locations.

The determined blade angles and chord lengths

are used as input data for the performance prediction

by through-flow analysis of the FANDAS code. The

present design optimization study also employs the

design constraints for design flow capacity, total

pressure, shaft power and flow angles angles,

solidities (chord length/blade spacing) of blade

sections at different radial locations. The design

variables and the design constraints of the present

optimization problem are summarized in Table 1.

Figure 7: Optimization scheme of axial flow fan.

Table 1: Design variables and constraints for axial fan

efficiency maximization.

Applying the present optimization technique to an

axial flow fan’s efficiency maximization problem of

Table 1, several iterative calculations are carried out

and the design variables and the design constraints are

converged during searching optimal design solution.

After the several iterative computations, optimal

design variables are obtained and the objective

function is finally calculated as shown in Table 2. The

optimal camber angle is higher than the initial design

over entire blade span while the optimal stagger angle

at hub is lower than the initial design, which is

optimal chord length is smaller than the initial design

and its magnitude decreases from tip to hub. Optimal

fan rotor blade geometry is constructed by the

FANDAS code with the design variables (refer to

Figure 8); the efficiency of optimal fan is improved

by 6.7 % when compared with the initial design.

Table 2: Optimal design variables and objective function.

Figure 8: Optimal fan rotor blade geometry.

Performance and Efﬁciency Improvement of an Axial Flow Fan by Combining the FANDAS and the PIAnO Codes

349

In order to verify the optimal fan design, CFD

modelling is also made with structured mesh system

in flow domain of the optimal fan stage (optimal fan

rotor with outlet guide vane) and numerical

calculations are carried out by the SIMERCIS MP

code (Kyungwon Tech, 2022) with MRF scheme and

k- turbulence model. Figures 9 and 10 show overall

total pressure and efficiency curves of optimal fan,

and the FANDAS predictions are matched well with

the CFD results. As shown in Figure 9, optimal fan

model shows lower total pressure at design point than

the design constraint (P

< 850 Pa) and wide

operation range from 2700 to 3700 m

/min. In Figure

10, the efficiency of optimal fan model is 85.8 %

which is fairly compared with the CFD result of 82.8

% and is much higher than the initial design of 79.1

% (refer to Table 2). Total efficiency of optimal fan

model is also maintained above 80% in wide flow

capacity range between 2700 and 4000 m

/min.

Figure 9: Total pressure curves of optimal fan.

Figure 10: Total efficiency curves of optimal fan.

As the setting angle of optimal fan rotor blade is

changed by adjusting the pitch angle from -5 to + 5

degree relative to the design setting angle (refer to

Table 2), the operation range, the performance and

the efficiency curves are moved into lower or higher

flow domain so the optimal fan can be operated with

high efficiency above 80% over wider flow capacity

range between 2000 and 5000 m

/min.

4 CONCLUSIONS

The present study provides a design optimization

method of axial flow fan, which combines the

FANDAS code for fan blade design and the PIAnO

code for optimization. Based on the FANDAS code,

a design optimization problem of axial flow fan is

formulated and solved with multiple design variables

and constraints by applying HMA algorithm of the

PIAnO code. Through the optimization of fan rotor

blade, fan efficiency is improved by 6.7 % relative to

the initial design and the optimal fan can be operated

with high efficiency over wide flow capacity range.

Furthermore, under variable-pitch operation, the

optimal fan can be operated with high efficiency over

wider flow capacity range.

ACKNOWLEDGEMENTS

This work was supported by the Korea Institute of

Energy Technology Evaluation and Planning

(KETEP) grant funded by the Korea government

Ministry of Trade, Industry & Energy(MOTIE),

Republic of Korea.

(No. 2021202080026).

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SIMULTECH 2023 - 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

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Performance and Efﬁciency Improvement of an Axial Flow Fan by Combining the FANDAS and the PIAnO Codes

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