Method to predicting optimal cabin operative temperature for civil aircraft

Pang, Liping; Wang, Yingjie; Liu, Meng; Helin, Zhang; Wang, Jun

doi:10.1016/j.buildenv.2013.08.002

Cited by 17 publications

(3 citation statements)

References 11 publications

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“…But for an aircraft cabin environment, its cabin pressure and RH are lower than normal specified standard [23][42] . Therefore, a corrected PMV model is used in this paper [43] . The value of RH is assumed as 30% considering the relatively dry cabin environment in our study.…”

Section: Objective Functionsmentioning

confidence: 99%

Optimization of air distribution mode coupled interior design for civil aircraft cabin

Pang

Bai

et al. 2018

Building and Environment

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The airflow distribution and thermal comfort of human beings in civil aircraft cabin are influenced by many factors such as the ventilation mode, ventilation air volume, and supply air temperature and so on. Among these factors, the choice of ventilation mode in the civil aircraft cabin is also restricted by the interior and aesthetic designs. Yet few researches noticed the impact of these designs on cabin air distribution. In this paper, an optimization design method for the air distribution mode of civil aircraft will be discussed based on Computational Fluid Dynamic (CFD) method and Micro-Genetic Algorithm (Micro-GA). Two interior design structures with different luggage bin and light band will be used to investigate their influence on the design of air distribution mode. In this optimization, the position of air supply inlets and the supply air angle are defined as the optimization variables. The Predicted Mean Vote (PMV) and the air age are specially chosen as the objective functions. The relevant regulations for cabin temperature uniformity are determined as the thermal constraint conditions. The study results show that the presented method can ensure the convergence of optimization process. The Pareto Optimal Frontiers (POFs) can be obtained from this multi-objective optimization. The POFs can present the relationship of two objective functions. The preferred air distribution mode coupled different interior designs can be efficiently recommended from the optimization

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Section: Objective Functionsmentioning

confidence: 99%

Optimization of air distribution mode coupled interior design for civil aircraft cabin

Pang

Bai

et al. 2018

Building and Environment

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“…In their research, Cheung et al [10] confirmed that Fanger's PMV model contains an accuracy of only 34% in its results. With the possibility of improving the prediction of thermal comfort sensations, many adaptive models have come to be developed, such as: Nguyen, Singh, and Reiter [11]; Liping et al [12]; Ruiz and Correa [13]; Gilani, Khan, and Ali [14]; Zhang et al [15]. Several adaptive thermal comfort studies have been conducted in numerous environments and countries, such as in housing in Japan [16], educational buildings in Mexico [17], and office buildings in Spain [18] and in Brazil [19].…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Thermal Comfort Models: Which One Is Suitable Model to Assess Thermal Reality in Brazil?

Niza

Broday

2022

Energies

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The Predicted Mean Vote (PMV) has discrepancies in relation to the thermal reality of the environment; thus, adaptive models serve to improve this estimate. In this context, this research aimed to verify the performance of PMV and adaptive models under different conditions in Brazil from an analysis of variance and to further classify individuals into clusters according to their feelings of thermal comfort. Through ASHRAE’s Global II Thermal Comfort Database, users of offices and classrooms in Brasilia, Recife, Maceió, and Florianópolis were investigated. The results of ANOVA showed that the PMV model did not represent the thermal reality of any of the cities investigated, and the cluster analysis showed how most people felt thermally in relation to indoor environments.

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“…For saving energy, Yang et al (2017) proposed a new environmental control system to change energy from the cabin- discharged air into shaft work. Liping et al (2013) introduced a method, which determines the optimal operative temperature in an aircraft cabin. A corrected Predicted Mean Vote (PMV) model and linear regressive analysis were used to calculate the optimal temperature.…”

Section: Introductionmentioning

confidence: 99%

Local thermal non-equilibrium conjugate forced convection and entropy generation in an aircraft cabin with air channel partially filled porous insulation

Çiçek

Baytaş

2021

AEAT

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Purpose The purpose of this study is to numerically investigate heat transfer and entropy generation between airframe and cabin-cargo departments in an aircraft. The conjugate forced convection and entropy generation in a cylindrical cavity within air channel partly filled with porous insulation material as simplified geometry for airframe and cabin-cargo departments are considered under local thermal non-equilibrium condition. Design/methodology/approach The non-dimensional governing equations for fluid and porous media discretized by finite volume method are solved using the SIMPLE algorithm with pressure and velocity correction. Findings The effects of the following parameters on the problem are investigated; Reynolds number, Darcy number, the size of inlet and exit cross-section, thermal conductivity ratio for solid and fluid phases, angle between the vertical symmetry axis and the end of channel wall exit and the gap between adiabatic channel wall and horizontal adiabatic wall separating cabin and cargo sections. Originality/value This paper can provide a basic perspective and framework for thermal design between the fuselage and cabin-cargo sections. The minimum total entropy generation number is calculated for various Reynolds numbers and thermal conductivity ratios. It is observed that the channel wall temperature increases for high Reynolds number, low Darcy number, narrower exit cross-section and wider the gap between channel wall and horizontal.

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Method to predicting optimal cabin operative temperature for civil aircraft

Cited by 17 publications

References 11 publications

Optimization of air distribution mode coupled interior design for civil aircraft cabin

Optimization of air distribution mode coupled interior design for civil aircraft cabin

An Analysis of Thermal Comfort Models: Which One Is Suitable Model to Assess Thermal Reality in Brazil?

Local thermal non-equilibrium conjugate forced convection and entropy generation in an aircraft cabin with air channel partially filled porous insulation

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