Inverse design of aircraft cabin environment using computational fluid dynamics-based proper orthogonal decomposition method

Abstract

To design a comfortable aircraft cabin environment, designers conventionally follow an iterative guess-and-correction procedure to determine the air-supply parameters. The conventional method has an extremely low efficiency but does not guarantee an optimal design. This investigation proposed an inverse design method based on a proper orthogonal decomposition of the thermo-flow data provided by full computational fluid dynamics simulations. The orthogonal spatial modes of the thermo-flow fields and corresponding coefficients were firstly extracted. Then, a thermo-flow field was expressed into a linear combination of the spatial modes with their coefficients. The coefficients for each spatial mode are functions of air-supply parameters, which can be interpolated. With a quick map of the cause–effect relationship between the air-supply parameters and the exhibited thermo-flow fields, the optimal air-supply parameters were determined from specific design targets. By setting the percentage of dissatisfied and the predicted mean vote as design targets, the proposed method was implemented for inverse determination of air-supply parameters in two aircraft cabins. The results show that the inverse design using computational fluid dynamics-based proper orthogonal decomposition method is viable. Most of computing time lies in the construction of data samples of thermo-flow fields, while the proper orthogonal decomposition analysis and data interpolation is efficient.

A New Optimization Design Method of Multi-Objective Indoor Air Supply Using the Kriging Model and NSGA-II

“…By analyzing some studies of CFD-based genetic algorithms [4,10,26,28,29,60,61] and POD methods [5,6,24,25,62], viewing the source code (such as Geatpy), and communicating with some of the authors, a summary of the three methods (including the method of this paper) was made, as shown in Table 6. Of course, the table analyzed only the simplest form of each method and did not include various types of variants, such as the co-evolution of multiple populations in genetic algorithms, where the gradient dependence comes from the continuity assumption and the interpolation method.…”

“…When designing air supply systems to create a comfortable environment, the design of air supply parameters is a very critical part of the process. Inverse design is currently a more effective design method than trial-and-error methods, where only forward methods (including the CFD-based adjoint method [1,2], the CFD-based genetic algorithm method [3,4], the proper orthogonal decomposition (POD) method [5], etc.) can be used to design the desired air environment, and the reverse methods can be used for traceability [6].…”

Fast prediction for indoor environment: Models assessment

“…Before applying POD in engineering, a series of CFD simulation should be conducted. 17 Most of the total computing time would be for CFD simulations, while the POD only requires several seconds to establish a new case. Due to its rapidity, the online control of indoor environment, such as in the aircraft cabin environment is possible using CFD-based POD method.…”

Challenges of using CFD simulation for the design and online control of ventilation systems

“…Thereby, 'low-dimension' can be interpreted as 'lower-resolution data' through volume-averaging indoor parameters (i.e., pollutant concentration) with acceptable resolution error, thus leading to much smaller data storage, tailored towards online monitoring and control for ventilation systems. Transient regimes can be solved by using a reduced-order LLVM, 14 to initiate fast prediction of Figure 1. The pollutant concentration distribution inside the ventilation enclosure obtained (a1, a2) using a highdimensional representation (RANS) and (b1, b2) using a LLVM.…”