E3S Web Conf.
Volume 85, 2019EENVIRO 2018 – Sustainable Solutions for Energy and Environment
|Number of page(s)||6|
|Published online||22 February 2019|
Integrated inverse design of ventilation for an aircraft cabin
School of Civil Engineering, Dalian University of Technology, Dalian 116024, China
2 Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm 100 44, Sweden
3 Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA
4 School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA
5 Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China
6 Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology (DUT), 2 Linggong Road, Dalian 116024, China
* Corresponding author: email@example.com
Cabin ventilation is crucial for maintaining thermal comfort and air quality for passengers and crew. The genetic algorithm, proper orthogonal decomposition (POD), and adjoint method have been proposed to inversely design the cabin ventilation. However, each method has its cons and pros. This paper proposed to integrate the above three methods in cascades. The genetic algorithm was applied first in the first stage to roughly circumscribe the ranges of design parameters. Then POD was applied in the next stage to further narrow the ranges and estimate the optimal parametric sets for each design criterion. The estimated optimal design from POD was supplied to the adjoint method for fine tuning. The air-supply parameters of a five-row aircraft cabin were inversely designed to achieve the minimum absolute value of the predicted mean vote (PMV) and the minimum averaged mean age of air. The results showed that the integrated method was able to improve the design stage by stage. The integrated method has superior advantages to assure the optimal design while minimizing the computing expense.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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