Abstract
This work presents multi-objective optimization of an aspirating smoke detection system which uses the pipeline to transport air sample from the sampling points to the analysing module. On the basis of 3D computational fluid dynamics simulation it has been shown that the smoke transport will not always take place in the centre of the pipe and that one dimensional analysis is not able to provide information in which layer smoke transport will take place. Consequently, velocity from the layer at the distance of 0.95R from the pipe centreline was taken as an input for calculation of the transport time to bind the calculation on the safe side. By employing the multi-objective optimization approach, balancing of specific transport time and volume flow at the sampling points’ location was achieved through pipeline configuration variation with respect to pipe diameters and the position of branches along the main pipe. Objective function was assembled from the flow rate function and transport time function using the weighted sum method. Results for five different values of weight factor have been discussed. After reaching weight factor value of 0.75, configuration reached requested sensitivity, and further increase of weight factor enabled more uniform flow across the network without deterioration of transport time.
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Abbreviations
- v, v avr (m/s):
-
Velocity, average velocity
- \(r,R\) (m):
-
Radius
- \(n\) (–):
-
Parameter
- Re (–):
-
Reynolds number
- \(a, \, b,{\text{ c}}\) (–):
-
Constants
- \(\nu\) (m2/s):
-
Kinematic viscosity
- \(h,h_{lin} ,h_{loc}\) (m):
-
Hydraulic head, hydraulic head of losses (linear and local)
- \(h_{12} ,h_{\bmod }\) (m):
-
Hydraulic head of the pipe, module head
- \(p\) (Pa):
-
Pressure
- \(\rho\) (kg/m3):
-
Density
- L (m):
-
Length of the pipe
- O vm(–):
-
Flow rate ratio
- Q (m3/s):
-
Volume flow
- Q m, Q v, Q f (m3/s):
-
Volume flow of module, fan and filter
- g (m/s2):
-
Gravity constant
- V, F, K (–):
-
Pressure loss coefficients of fan, filter and chamber
- d (m):
-
Pipe diameter
- t, t avr , t 0.95 , (s):
-
Time, mean time, time near wall
- t nor (–):
-
Normalized transport time
- T avr (s):
-
Sum of mean times
- K (–):
-
Parameter
- x, y, z (m):
-
Cartesian coordinates
- r (m):
-
Vector from origin to curve point
- s x , s y , s z (m):
-
Component of direction vector
- f, f t, f Q (–):
-
Dimensionless objective functions
- A (–):
-
Matrix of inequality constrain
- d, x (m):
-
Vector of project variables
- CFL (–):
-
Courant–Friedrichs–Lewy number
- w (–):
-
Weighing factor
- y (kg/kg):
-
Mass fraction
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Acknowledgements
This research was funded under the auspice of the European Regional Development Fund, Operational Programme Competitiveness and Cohesion 2014-2020, project number KK.01.1.1.04.0070.
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Višak, T., Baleta, J., Virag, Z. et al. Multi objective optimization of aspirating smoke detector sampling pipeline. Optim Eng 22, 121–140 (2021). https://doi.org/10.1007/s11081-020-09582-z
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DOI: https://doi.org/10.1007/s11081-020-09582-z