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To attain high-performance ejector configurations, an ejection characteristic testing system was established initially to validate the reliability of the Realizable k-εturbulent model. Subsequently, optimization investigations were conducted on lobed nozzle ejectors with various structural parameters. The effects of four key structural parameters, including lobed nozzle expansion angle α, lobed nozzle width d, number of lobes in the nozzle n, and height of the square-to-circle section h, were systematically studied. Furthermore, the CRITIC method was employed for multi objective evaluation to identify the optimal design configuration for the casing ejector. The research findings revealed that among the structural parameters, the lobed nozzle expansion angle α exerted the greatest influence on the ejection coefficient and pressure loss coefficient. The weights of the evaluation criteria were determined by the CRITIC method as follows: ejection coefficient (49.38%) < pressure loss coefficient (50.62%). The optimal design configuration determined by the CRITIC method included α = 45°, d = 150 mm, n = 14, and h = 600 mm. The resulting enclosure design ensures smooth airflow within the system, preventing the backflow of high temperature mainstream fluid and heating the enclosure. It also maintains a temperature distribution in the typical cross-section that meets specified requirements. Additionally, it facilitates improved mixing of mainstream and secondary fluid and reduces exhaust gas temperature. [ABSTRACT FROM AUTHOR]

In this research, the escalating energy consumption challenges in data centers are addressed by optimizing airflow organization designs. Through the use of computational fluid dynamics (CFD) simulations, three different airflow strategies were evaluated and improved: underfloor precision air conditioning, inter-column air conditioning, and backplane air conditioning. These cooling systems, which are usually considered in isolation, were compared in a comprehensive manner to get a full picture of their efficiency and effectiveness. The findings reveal that the implementation of cold aisle containment (CAC) or hot aisle containment (HAC) significantly improves air supply efficiency (ASE) and reduces the supply heat index (SHI), leading to a more uniform temperature distribution and enhanced cooling performance. Specifically, the ASE increased from 65.69% to 85.57% and 90.25% for underfloor precision air conditioning and from 71.29% to 92.16% and 92.17% for inter-column air conditioning, with corresponding reductions in SHI. The backplane cooling system offered consistent ambient temperatures throughout the room, eliminating thermal hotspots without the need for aisle containment. This study offers a comparative analysis of different airflow organization schemes, highlighting the benefits of aisle containment in precision and inter-column air conditioning and the suitability of backplane air conditioning for high-density cooling without the need for traditional aisle separation. The results are crucial for informing energy-efficient cooling strategies in data center design and operation. [ABSTRACT FROM AUTHOR]

To meet the requirements of achieving higher efficiency and lower NOx pollution, the flame temperature in gas turbine combustors increases continually; thus, the effusion-cooling technology has been used to ensure the combustor liner remains within the allowed temperature, by which the combustion characteristics and emission behavior are possibly influenced. In order to investigate the effects of dome cooling air flow on combustion characteristics and NOx emissions, three-dimensional combustion simulations for a swirl-stabilized can-type gas turbine combustor are carried out in this work by using the computational fluid dynamics (CFD) method. Through adjusting the ratio of the dome cooling air flow and the dilution cooling air flow, the characteristics of flow field, temperature distribution and NOx emissions under each work condition are analyzed. At different ratios of the dome-cooling air flow to the total air flow, the flow velocity field in the region near the center of the combustion chamber is not changed much, while the velocity field near the chamber wall shows a more significant difference. The temperature in the outer recirculation zone within the combustion chamber is effectively reduced as the dome cooling air flow increases. By analyzing the distribution characteristics of the concentration of OH*, it is demonstrated that the dome cooling air flow does not have a direct effect on the reaction of combustion. It is also found that as the ratio of the dome cooling air flow to the total air flow increases from 0 to 0.15, the value of the NOx emissions drops from 28.4 to 26.3 ppmv, about a 7.4% decrease. The distribution of the NOx generation rate in the combustion chamber does not vary significantly with the increasing dome cooling air flow. Furthermore, by calculating the residence time in different stages, when the the ratio of the dome cooling air flow to the total air flow varies from 0 to 0.15, the residence time in the pilot stage decreases obviously, from 42 ms to 18 ms. This means that reduction in residence time is the main factor in the decrease of NOx emissions when the dome cooling air flow increases. [ABSTRACT FROM AUTHOR]

(1) Background: With the rapid development of cloud computing, large AI models, and other emerging technologies, the issue of heat dissipation in data centers has become increasingly prominent. This issue is often caused by inappropriate temperature distribution when using cold air to cool servers. Improving temperature distribution is key to optimizing the thermal performance of data centers. Previous solutions do not include installing adjustable underfloor deflectors under a raised floor while adjusting the aperture ratio of the floor grille and replacing the side of the floor grille located near the air-conditioning unit with a fan floor. (2) Methods: A 3D model of a data center was established, and its meshing and boundary conditions were set. The airflow inside the data center was analyzed using a CFD simulation to assess the temperature distribution resulting from two proposed solutions. (3) Results: Simulations and analyses showed that both options balanced the airflow close to and away from the conditioned side cabinets. This maximized the cooling capacity and improved temperature uniformity. The maximum temperature drop registered for the average cabinet's out temperature was 2.81 °C. And by installing an adjustable underfloor deflector under the floor grille in rows O and N and adjusting the grille opening, the airflow to the cabinet near the air-conditioned side increased by 18.1%, and the airflow away from the air-conditioned side decreased by 5.1%. Similarly, replacing the Q-row floor grille with a fan floor resulted in a 4.9% increase in airflow to the cabinet near the air-conditioning side and a 3.8% decrease in airflow to the cabinet away from the air-conditioning side. (4) Conclusions: Airflow is a crucial factor that affects cabinet temperature. And balancing airflow between the front-end and rear-end cabinets is essential to make the best use of the cooling capacity and improve temperature distribution within data-center cabinets. This can be achieved by installing a fan floor and an underfloor deflector device in front of high-temperature cabinets located near air-conditioning units. [ABSTRACT FROM AUTHOR]

In order to solve the problem of uneven distribution of air conditioning temperature and air velocity in the ward, it is easy to produce the uncomfortable feeling of cold and hot and wind blowing. Taking the standard double room general ward of a newly built hospital as the research object, a mathematical model was established, and CFD software was used to numerically simulate the temperature field and velocity field of the air in the ward, optimize the location of the air outlet, and put forward the suggestion of the optimal installation location of the hospital bed. The results show that when the fan coiler air supply outlet is close to the west wall and the fresh air outlet is far away from the west wall, the inhomogeneity of the distribution of the temperature field and velocity field in the ward is reduced, and at this time, the temperature and velocity distribution of the air in the ward is more uniform, so that the patients' overall feeling in the ward is more comfortable, and at this time, the installation position of the air outlet is more reasonable; and it is determined that the optimal placement of the beds in the room is at the locations of x = 2 m, y = 2.5 m and x = 2 m, y = 4.5 m, and at this time the two beds are at the same time, which is more reasonable. When y = 4.5 m, the temperature difference between the two beds is less than 0.5 K, the wind speed difference is not more than 0.08 m/s, and the velocity gradient direction is the same. [ABSTRACT FROM AUTHOR]

Predicting indoor airflow distribution in multi-storey residential buildings is essential for designing energy-efficient natural ventilation systems. The indoor environment significantly impacts human health and well-being, considering the substantial time spent indoors and the potential health and safety risks faced daily. To ensure occupants' thermal comfort and indoor air quality, airflow simulations in the built environment must be efficient and precise. This study proposes a novel approach combining Computational Fluid Dynamics (CFD) simulations with machine learning techniques to predict indoor airflow. Specifically, we investigate the viability of employing a Deep Neural Network (DNN) model for accurately forecasting indoor airflow dispersion. The quantitative results reveal the DNN's ability to faithfully reproduce indoor airflow patterns and temperature distributions. Furthermore, DNN approaches to investigate indoor airflow in the residential building achieved an 80% reduction in the time required to anticipate testing scenarios compared with CFD simulation, underscoring the potential for efficient indoor airflow prediction. This research underscores the feasibility and effectiveness of a data-driven approach, enabling swift and accurate indoor airflow predictions in naturally ventilated residential buildings. Such predictive models hold significant promise for optimizing indoor air quality, thermal comfort, and energy efficiency, thereby contributing to sustainable building design and operation. [ABSTRACT FROM AUTHOR]

The burner is central to the thermal management of solid oxide fuel cell (SOFC) system. Using cooling air bypass (CA) into burner is simple and effective to control the excessive temperature. A novel theoretical model for SOFC systems equipped with CA into burner is developed and verified with multiple experimental data. A comprehensive control-parameter classification analysis is carried out with the model, revealing quantitatively the impacts of the fuel utilization (U f), air flow rate (V a i r ), and maximum burner temperature (T B M ), on the system performance. The results confirm CA can minimize thermal shock to the stack. Favorable combinations of (U f , V a i r , T B M ) satisfying the thermal constrains of maximum cell temperature and temperature difference are identified, and capable of achieving a system alternating current efficiency of 55 % or more. The theoretical model can help the system design optimization targeting the specifics of the stack. • System model describing all component processes and validated by multiple experiments. • Parametric study characterizing impacts of control parameters on system performance. • Role of cooling air bypass into burner on reducing stack thermal shock illustrated. • Importance of air flow rate on stack temperature and system efficiency demonstrated. • Combinations of system parameters for high efficiency and safe operation identified. [ABSTRACT FROM AUTHOR]

• The effect of coolant preheating strategy on cold start performance is investigated. • One-dimensional model of fuel cell systems is established by AMESim software. • The accuracy of the model is verified by corresponding cold start experiments. • Air inlet temperature, air inlet flow rate, and heating power effects are clarified to improve the cold start performance. The rapid cold start capability of fuel cell vehicles in low-temperature environments is one of the key factors restricting their commercialization. Reasonable and effective strategies are crucial to improving the low-temperature cold start capability of fuel cell vehicles. In this paper, a cold start model of fuel cell system is established, and the model is verified based on the cold start experiment of a hybrid fuel cell vehicle. The necessity of the coolant preheating strategy in the cold start is analyzed, and the important role of the coolant preheating strategy in helping the fuel cell system to start quickly at -10°C and below is demonstrated. Furthermore, the effects of air inlet temperature, air inlet flow rate, and external heater power on the cold start performance are investigated. The results show that when the air inlet temperature rises from -13°C to 65°C, the start time is shortened from 279 s to 234 s (reduced by 16.13 %). And at low air inlet temperatures, the lower flow rate of air can significantly reduce the temperature difference and maintain uniformity of temperature inside the stack, while at a higher temperature, the higher air flow rate causes the temperature of the cell stack to rise rapidly. For heating power, the start time is shortened from 421 s to 126 s (reduced by 70.07 %) when the heating power is increased from 3 kW to 11 kW. However, it will cause a larger temperature difference between the inlet and outlet of the coolant, which is not conducive to the uniform distribution of the temperature inside the stack. Thus, the start time can be shortened by increasing the air inlet temperature, air inlet flow rate, and heating power with the consideration of the temperature difference that the stack can withstand. The model developed by this study provides an effective way to analyze the fuel cell system during cold start, which is useful for the development of control strategies in the future. [ABSTRACT FROM AUTHOR]

Turbine-based combined cycle (TBCC) engines are characterized by strong nonuniformity flow in the turbine outlet and mode transition involving multiple bypasses, which may lead to failure of mode transition. In this paper, the mixing characteristics and flow losses of a TBCC multibypass combustor with a double-mixer configuration under nonuniform velocity and temperature inlet conditions are investigated through numerical simulation. The results show that the antiphase double-lobed mixer has a higher mixing efficiency than the in-phase double-lobed mixer at x/h < 0.8 (x/h are dimensionless axial coordinates), and the total pressure loss is greater; moreover, the mixing efficiency is reversed, and the total pressure loss is basically the same at x/h > 0.8. For both nonuniform velocity and temperature conditions, the mixing efficiency at peak profiles less than 50% is lower than that at the uniform inlet. With increasing velocity nonuniformity, the total pressure loss cost of increased mixing characteristics increases. The effect of the variation in the airflow velocity in the combustor on the total pressure loss is greater than that of the variation in airflow mixing characteristics when the mass flow rate in the combustor is changed. The change in mixing characteristics caused by the nonuniform temperature inlet profile is due to the temperature distribution and is independent of the type and performance of the mixer. [ABSTRACT FROM AUTHOR]