Experimental study of transient air distribution of a jet collision region in an aircraft cabin mock-up

Li, Jiayu; Liu, Junjie; Cao, Xiaodong; Jiang, Nan

doi:10.1016/j.enbuild.2016.06.039

Cited by 32 publications

(24 citation statements)

References 20 publications

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“…The measurement points were distributed along the large-scale circulation flow trajectories. The large-scale circulations have unsteady characteristics in the cabin, and the transient airflow patterns are also changeable [ 34 ]. In order to experimentally explore the representative position of turbulent kinetic energy spectrum analysis in the cabin, two case comparisons were performed in this study.…”

Section: Methodsmentioning

confidence: 99%

Experimental investigation of large-scale flow structures in an aircraft cabin mock-up

Zhang

Liu

et al. 2020

Building and Environment

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The purpose of this study was to investigate the influence of large-scale circulation on the flow field in a cabin mockup. The velocity was measured by ultrasonic anemometers (UA). Then, this study analyzed the turbulence kinetic energy spectra of the velocity fluctuation signal. The turbulence kinetic energy spectra of the measurement points reflect the flow characteristic of the large-scale circulation in the cabin mockup. The results contribute to the understanding of the role of the thermal plume on the large-scale circulation in the cabin. The large-scale circulation's impact on air quality was also investigated, and the contaminant distribution was measured using tracer gas in the cabin. The two large-scale circulation interactions made the air flow mixing approximately uniform.

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Section: Methodsmentioning

confidence: 99%

Experimental investigation of large-scale flow structures in an aircraft cabin mock-up

Zhang

Liu

et al. 2020

Building and Environment

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“…Therefore, this air supply system is commonly used in the cabin. Li and Liu [41] found that this mode of supplying air at side walls and exhausting in both sides near the floor will result in two-jet collision regions with unsteady characteristic in cabin through PIV test. This is very typical in the sense that a fixed boundary condition results in dynamically changing airflow field in a built environment.…”

Section: Methodsmentioning

confidence: 99%

Inverse modeling of indoor instantaneous airborne contaminant source location with adjoint probability-based method under dynamic airflow field

Wang

Cheng

et al. 2017

Building and Environment

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Accurate and prompt identification of airborne contaminant source location in indoor environment is of vital importance for building operation safety. Successful inverse tracking algorithm to identify airborne contaminant location usually requires limited sensor readings and indoor airflow information as input. Such mathematical algorithm under steady-state indoor airflow scenario has been intensively investigated. However, in many built environment scenarios, air velocity direction and magnitude keeps changing with time, making the transportation process of airborne contaminant significantly different from it under steady-state airflow. This paper mainly focuses on the airborne contaminant source location identification under dynamic airflow, by employing an adjoint probability-based inverse tracking method. The mathematical model and process of indoor instantaneous contaminants source location identification under dynamic air flow field is investigated and presented. Case studies using Computational Fluid Dynamics (CFD) tool by unsteady RANS simulation are conducted on a subway station model as well as an aircraft cabin, in which case experimental validation is also conducted. The capability of the new method is verified for air contaminant source location identification under dynamic indoor airflow. Successful identification of airborne contaminant source location dynamic airflow field implies the capability of the method to locate an airborne contaminant source by limited sensor information and time-dependent airflow field in real-time. Practically the timedependent airflow field data can be obtained through CFD simulation with unsteady RANS model and monitored time-dependent boundary condition.

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“…The proper orthogonal decomposition method was first proposed by Kosambi [30], and it has since been successfully applied in a variety of engineering fields, such as image processing, signal analysis, data compression, and recently equally in building physics [26,[31][32][33][34][35]. POD is also known as Karhunen -Loeve decomposition, principal component analysis, or singular value decomposition, and the connections of the methods are provided by [36].…”

Section: Proper Orthogonal Decompositionmentioning

confidence: 99%

Model order reduction for efficient deterministic and probabilistic assessment of building envelope thermal performance

Hou

Roels

Janssen

2020

Energy and Buildings

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To lessen the computational expense of building energy simulations, the potential of model order reduction methods for assessing building envelope thermal performance is assessed, through both deterministic and probabilistic case studies of modelling heat transfer through a massive masonry wall. More specifically, two model order reduction methodsproper orthogonal decomposition (POD) and proper generalized decomposition (PGD)are investigated: therefore their calculation accuracies and computational costs are compared with a standard finite element method (FEM). The outcomes show that the POD model strongly outperforms the PGD and FEM models when deterministically simulating wall heat transfer. Additionally, the use of POD to simulate a problem differing from the training simulation can provide an accurate result, and hence the robustness and flexibility of POD is confirmed. This advantage thus expands the application scope of POD for simulating building envelope thermal performance with variable input parameters, rendering it excellent to replace a time-consuming original model in the probabilistic analysis. For the probabilistic case study, it is shown that the sampling errors are much more dominant in the accuracy, implying that the deterministic accuracy of the different models plays a much smaller role, and hence has a very limited effect on the overall convergence behavior of different models. Therefore, the use of POD with a smaller number of modes is strongly suggested in probabilistic analyses to reduce the overall computational expense as much as possible.

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Experimental study of transient air distribution of a jet collision region in an aircraft cabin mock-up

Cited by 32 publications

References 20 publications

Experimental investigation of large-scale flow structures in an aircraft cabin mock-up

Experimental investigation of large-scale flow structures in an aircraft cabin mock-up

Inverse modeling of indoor instantaneous airborne contaminant source location with adjoint probability-based method under dynamic airflow field

Model order reduction for efficient deterministic and probabilistic assessment of building envelope thermal performance

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