AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Building Simulation Article
Article Link
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article

Determination of the optimal control parameter range of air supply in an aircraft cabin

Xianglong Hu1,2, Xue-yi You1,2( )
School of Environmental Science and Engineering, Tianjin University, Tianjin, China
Tianjin Key Lab. of Indoor Air Environmental Quality Control, Tianjin, China
Show Author Information

Abstract

Comfortable and healthy aircraft cabin environment is required as more and more people choose to travel by air. The cabin environment is optimized by searching the optimal control parameters such as air supply velocity, angle and temperature. The optimal solutions are obtained by combining a multi-objective particle swarm optimization (MOPSO) with the simulation of computational fluid dynamics (CFD). It is found that different combinations of optimal air supply parameters can build an optimal cabin environment and the locations of the obtained optimal solutions are isolated in their value spaces. To achieve a stable engineering control operation, the determination of a stable range of optimal air supply parameters is required. Therefore, a method by using cluster analysis is developed to obtain stable ranges of optimal air supply parameters. Results show that the proposed method can obtain the ranges of optimal air supply parameters successfully.

Keywords

particle swarm optimizationmulti-objective optimizationcluster analysiscabin environmentstable rangeoptimal air supply parameters

References

 
JE Alvarez-Benitez, RM Everson, JE Fieldsend (2005). A MOPSO algorithm based exclusively on pareto dominance concepts. In: CAC Coello, AH Aguirre, E Zitzler (eds), Evolutionary Multi-Criterion Optimization, 3rd International Conference on EMO, pp. 459-473. Berlin: Springer.
Crossref
 
ASHRAE (2004). Thermal environmental conditions for human occupancy. In: ANSI/ASHRAE Standard 55-2004. Atlanta, USA: ASHRAE.
 
Q Chen (1995). Comparison of different k-ε models for indoor air flow computations. Numerical Heat Transfer, Part B Fundamentals, 28: 353-369.
Crossref Google Scholar
 
CAC Coello, GT Pulido, MS Lechuga (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8: 256-279.
Crossref Google Scholar
 
E Elbeltagi, T Hegazy, D Grierson (2005). Comparison among five evolutionary-based optimization algorithms. Advanced engineering informatics, 19: 43-53.
Crossref Google Scholar
 
N Gao, J Niu (2008). Personalized ventilation for commercial aircraft cabins. Journal of aircraft, 45: 508-512.
Crossref Google Scholar
 
ISO (2005). Ergonomics of the thermal environment—Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria. In: ISO 7730: 2005(en). Geneva: International Standardisation Organisation.
Google Scholar
 
L Kaufman, PJ Rousseeuw (2009). Finding groups in data: An introduction to cluster analysis (Vol. 344): Hoboken NJ, USA: John Wiley & Sons.
 
J Kennedy, R Eberhart (1995). Particle swarm optimisation. In: Proceedings of IEEE International Conference on Neural Networks, Perth WA, USA, pp. 1942-1948.
 
T Lindgren, D Norbäck (2005). Health and perception of cabin air quality among Swedish commercial airline crew. Indoor Air, 15: 65-72.
Crossref Google Scholar
 
W Liu, J Wen, J Chao, W Yin, C Shen, D Lai, C-H Lin, J Liu, H Sun, Q Chen (2012). Accurate and high-resolution boundary conditions and flow fields in the first-class cabin of an MD-82 commercial airliner. Atmospheric Environment, 56: 33-44.
Crossref Google Scholar
 
J Ojima (2009). Laboratory evaluation of carbon monoxide exposure in CO2 arc welding. Journal of occupational health, 51: 377-379.
Crossref Google Scholar
 
L Pang, Y Wang, M Liu, H Zhang, J Wang (2013a). Method to predicting optimal cabin operative temperature for civil aircraft. Building and Environment, 69: 160-170.
Crossref Google Scholar
 
L Pang, J Xu, L Fang, M Gong, H Zhang, Y Zhang (2013b). Evaluation of an improved air distribution system for aircraft cabin. Building and Environment, 59: 145-152.
Crossref Google Scholar
 
V Pareto (1964). Cours d'economie politique. Geneva: Librairie Droz.
Crossref
 
J Seo, J Park, Y Choi (2013). Numerical study on human model shape and grid dependency for indoor thermal comfort evaluation. Journal of Mechanical Science and Technology, 27: 397-405.
Crossref Google Scholar
 
NR Tayebi, FM Nejad, M Mola (2013). Comparison between GA and PSO in analyzing pavement management activities. Journal of Transportation Engineering, 140: 99-104.
Crossref Google Scholar
 
M Wetter, J Wright (2004). A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization. Building and Environment, 39: 989-999.
Crossref Google Scholar
 
Y Xue, ZJ Zhai, Q Chen (2013). Inverse prediction and optimization of flow control conditions for confined spaces using a CFD-based genetic algorithm. Building and Environment, 64: 77-84.
Crossref Google Scholar
 
R Yang, L Wang (2012). Multi-objective optimization for decision-making of energy and comfort management in building automation and control. Sustainable Cities and Society, 2: 1-7.
Crossref Google Scholar
 
T-h Zhang, X-y You (2014). A simulation-based inverse design of preset aircraft cabin environment. Building and Environment, 82: 20-26.
Crossref Google Scholar
 
T Zhang, QY Chen (2007). Novel air distribution systems for commercial aircraft cabins. Building and Environment, 42: 1675-1684.
Crossref Google Scholar
 
Z Zhang, W Zhang, ZJ Zhai, QY Chen (2007). Evaluation of various turbulence models in predicting airflow and turbulence in enclosed environments by CFD: Part 2—Comparison with experimental data from literature. HVAC&R Research, 13: 871-886.
Crossref Google Scholar
Building Simulation
Volume 8 Issue 4,
August 2015
Pages 465-476
DOI: 10.1007/s12273-015-0225-8
Cite this article:
Hu X, You X-y. Determination of the optimal control parameter range of air supply in an aircraft cabin. Building Simulation, 2015, 8(4): 465-476. https://doi.org/10.1007/s12273-015-0225-8

524

Views

10

Crossref

N/A

Web of Science

13

Scopus

2

CSCD

Altmetrics
Received: 20 January 2015
Revised: 01 March 2015
Accepted: 18 March 2015
Published: 10 April 2015
© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2015
Return