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A novel ant lion optimizer-salp swarm algorithm for inverse heat conduction problem in pipeline fluid temperature recognition

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Abstract

In this paper, the inverse heat transfer problem is studied in a two-dimensional cross-section of a horizontal pipe to estimate the unknown time-varying fluid temperature close to the inner wall of the pipe. The uneven mixing of fluids at different temperatures leads to temperature fluctuations in the inner wall of the pipeline, which could result in wall stress changes and structural thermal fatigue. An inversion algorithm based on the ant lion optimizer-salp swarm algorithm (ALO-SSA) is proposed. The temperature data are utilized as input data for the inverse heat transfer problem (IHCP). The fluid temperature fluctuations are most dramatic near the inner wall at 0° and 30°. ALO-SSA algorithm exhibits significantly lower average error compared to the other two contrasting algorithms, with an estimated average error of 0.0395 at 0° and 0.0413 at 30° for temperature estimation. Experimental analysis showed that the algorithm has good speed and accuracy for solving similar inverse heat transfer problems.

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Abbreviations

T :

Temperature

r :

Radius

θ :

Angle

τ :

Time

∆τ :

Time step

ρ :

Density

c :

Specific heat capacity

λ :

Thermal conductivity

n :

Normal vector

h f,in :

Inner convection heat transfer coefficient

h f,out :

Outer convection heat transfer coefficient

T f,in :

Fluid temperature

T f,out :

Ambient temperature

T w :

Wall temperature

T 0 :

Initial temperature of the pipe

J :

Wall temperature

T Est,m,n :

Estimated temperature

T Exp,m,n :

Experimental temperature

N :

Population size

D :

Dimension

X :

Population position of ant

Fitness (x):

Fitness function

t :

Current number of iterations

i :

The ith individual

I :

Proportion of traps

X_AL:

Population position of ant lion

X best :

Optimal individual

μ :

Chaos parameter

ub:

Upper bound

lb:

Lower bound

I_real:

Real iteration

I_current:

Current iteration

I_factor:

Iteration factor

I_MAX:

Max iteration

F j :

Optimal position

c 1 c 2 c 3 :

Random numbers

j :

jth individual

IHCP:

Inverse heat conduction problem

DHCP:

Direct heat conduction problem

ALO:

Ant lion optimizer

SSA:

Salp swarm algorithm

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Authors and Affiliations

  1. School of Control and Mechanical, Tianjin ChengJian University, Tianjin, 300384, China

    Shoubin Wang, Jie Song, Guili Peng & Yunlong Li

  2. School of Instrument Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Yuan Zhou

Authors
  1. Shoubin Wang
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  2. Jie Song
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  3. Guili Peng
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  4. Yunlong Li
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  5. Yuan Zhou
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Correspondence to Guili Peng.

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Wang, S., Song, J., Peng, G. et al. A novel ant lion optimizer-salp swarm algorithm for inverse heat conduction problem in pipeline fluid temperature recognition. J Therm Anal Calorim 149, 173–185 (2024). https://doi.org/10.1007/s10973-023-12743-8

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  • DOI: https://doi.org/10.1007/s10973-023-12743-8

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