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![Thermal displacement ventilation system characteristics [24].](publication/313779862/figure/fig2/AS:651113309143041@1532248918459/Thermal-displacement-ventilation-system-characteristics-24.png)
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![Figure 2. Thermal displacement ventilation system characteristics [24].](publication/313779862/figure/fig2/AS:651113309143041@1532248918459/Thermal-displacement-ventilation-system-characteristics-24_Q320.jpg)
This paper is concerned with the development of a high-resolution and control-friendly optimization framework in enclosed environments that helps improve thermal comfort, indoor air quality (IAQ), and energy costs of heating, ventilation and air conditioning (HVAC) system simultaneously. A computational fluid dynamics (CFD)-based optimization metho...
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... is known, for displacement ventilation systems, a vertical temperature gradient should exist because it indicates a stratified airflow pattern and vertical stratification of contaminants. Consequently, two distinct zones are formed for TDVS (Figure 2): a lower occupied zone with little or no recirculation flow, and an upper zone with recirculation flow [24]. The simplified temperature profile in the space is already well understood by many previous studies. ...
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... Multi-objective optimization of the response parameters was performed by integration of RSM and NSGA-II. NSGA-II, a widely used multi-objective evolutionary algorithm is an improved version of NSGA and overcomes limitations such as computational complexity, lack of elitism, and selection of optimal parameter value for sharing parameter [62]. NSGA-II applies binary tournament selection, elitist preserving strategy, non-dominated sorting, and crowding distance mechanism to obtain a good quality and uniformly spread nondominated solution set [63]. ...
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... Li等人 [23] [27] . PMV) [28] 、由通风引起的预测不满意率(percent dissatisfied due to draft, PD) [29] 、平均空气龄τ [5] 、通风效 率 [30] 、冷热负荷 [31] 、能耗等. 针对不同的实际问题, 可 [49,50] 、POD方法 [51,52] 、ANN 方法 [53] 、伴随方法 [54,55] (2) 防范恐怖袭击与突发疫情防控. ...
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The vertical pipe intake-outlet plays an important role in the pumped hydro energy storage (PHES), and its main parameters included the orifice height ratio (H*), the diffuser short semi-axis ratio (a*), the diffuser long semi-axis ratio (b*) and the cover plate radius ratio (Rc*). The aim of this study was to analyse effects of the parameters and obtain the optimal design. An integration method combining computational fluid dynamics (CFD), response surface methodology (RSM) and genetic algorithm was proposed. To evaluate grid independency, the grid converge index was introduced. Based on the validation for the baseline design (H* = 0.577, a* = 1.087, b* = 4.231 and Rc* = 1.635), a reliable CFD model was developed to obtain results of sample points. Then RSM models were constructed and assessed, and contribution and interactions of the parameters were analyzed. Finally, the optimal design (H* = 0.422, a* = 1.177, b* = 5.363 and Rc* = 2.115) was obtained. The CFD results show that the overall head loss coefficient, the inflow and the outflow velocity distribution coefficient are reduced by 4.687%, 11.765% and 38.596%, respectively. Especially, the negative velocity at the trashrack section in the pump mode is eliminated. The improvement demonstrates that the proposed method achieves significant superiority over the trial-and-error method traditionally adopted in the intake-outlet design.
Proper selection and sizing of ventilation systems require knowledge of emissions from internal contaminant and heat sources and an understanding of the characteristics of air and contaminant movement. In this chapter, the major factors affecting air and contaminant movement inside ventilated space are summarized and classified as: (1) transport mechanism of contaminant in ventilated space; (2) contaminant sources; (3) forced convection or supply air jets introduced into the room by mechanical or natural ventilation systems, or their combination; (4) free convection flows along heated and cooled vertical surfaces and above heat sources; (5) airflow created in the vicinity of local and general exhausts; (6) aerodynamic means of large opening protection; and (7) airflow through intended and unintended openings and cracks in the building envelope. This chapter provides some guidance on how to select predominant factors affecting air and contaminant movement, account for their joint effects, and predict airflow characteristics.
To create a healthy and comfortable aircraft cabin, air-supply parameters of the cabin ventilation system must be designed appropriately. Several methods, such as the computational fluid dynamics (CFD)-based genetic algorithm, CFD-based adjoint method and CFD-based proper orthogonal decomposition (POD), have been developed in recent years for conducting an inverse design. The target environmental performance is specified first, and then the corresponding air-supply parameters are inversely solved with the use of a particular method. However, each method has its pros and cons in terms of efficiency and accuracy. To expedite the inverse design process, this study proposed to integrate the above three methods. The genetic algorithm was adopted first to circumscribe ranges of the air-supply parameters. Next, POD was applied to further narrow the ranges and estimate the optimal air-supply parameters for each design criterion. Finally, the estimated optimal design from POD was supplied to the adjoint method for fine tuning. The above strategy was applied to a five-row aircraft cabin to determine the air-supply opening sizes, directions and temperatures. Criteria that had been proposed specifically for aircraft cabins were used as design targets. Results show that the proposed integration was able to provide the optimal design for each design target. The integrated optimal design was superior to the design provided by each individual method. The bottleneck in further acceleration of the integrated design was the hundreds of design cases resolved by full CFD simulation.
