Air Supply Parameters Research Articles

Prompt design of the air-supply opening size for a commercial airplane based on the proper orthogonal decomposition of flows

Air supply is crucial for creating an acceptable air distribution inside aircraft cabins. To determine proper air-supply parameters, a conventional design has to solve many cases to obtain the flow patterns for each air-supply parameter, which is time-consuming. This study proposed a proper orthogonal decomposition (POD) of the flows to accelerate the design. A few original thermo-flow data samples are obtained using a full CFD simulation, and then the orthogonal spatial modes and their coefficients are extracted from these data samples. A trial and data sample increase scheme is used to determine whether the CFD-provided data samples are sufficient. A shape-preserving interpolation is applied to estimate the coefficients of the spatial modes between two neighboring data samples. With a quick map of the thermo-flow fields, the proper air-supply parameters can be rapidly determined based on the specific design criteria. The proposed method was applied to determine the size of an air-supply opening in a three-dimensional aircraft cabin, with the percentage of dissatisfied (PD), the predicted mean vote (PMV) and the mean age of air as the design criteria. The results show that the POD-based design is able to construct the field data with generally good accuracy. The inversely determined air-supply opening sizes between the proposed method and the full CFD simulation are quite similar. Future research may explore a better coordination between the original data sample preparation using the full CFD simulation and the interpolation of the coefficients of the spatial modes to further reduce the computing time.

Technical feasibility of a stratum-ventilated room for multiple rows of occupants

This study aimed to explore the technical feasibility of stratum ventilation for a room with occupants in multiple rows. Theoretical analysis, human subject tests and computational fluid dynamics (CFD) simulations were conducted. All the results showed that stratum ventilation can be used for a room with multiple rows of occupants. Human subject tests indicated that the acceptable thermal comfort with low draft was achieved for the two rows of occupants. The CFD simulations showed that the acceptable thermal comfort level has been reached, measured by EDTS (effective draft temperature for stratum ventilation), PMV (predicted mean vote), PPD (predicted percentage dissatisfied) and PD (percentage dissatisfied due to draft), and air of young age was also achieved for the three rows of occupants. This is because the cool fresh supply air can flow around and over the front-row occupants to reach the back rows even though they establish a local blocking effect to the supply airflows. Thus, the number of rows should not be a decisive factor for stratum ventilation. Therefore, it is reasonable to expect that with properly designed air supply parameters, stratum ventilation can be applied in a room with multiple rows of occupants.

Inverse design of the thermal environment in an airliner cabin by use of the CFD-based adjoint method

The current thermal environments in airliner cabins may not provide satisfactory comfort levels, and the design of these environments should be improved. This study aimed to design a desirable thermal environment for a single-aisle airliner cabin and used the CFD-based adjoint method to find the optimal design variables of air supply locations, size, and parameters. The design variables are used as the boundary conditions for solving the Navier–Stokes equations. By setting the occupant region as the design domain with a minimal predicted mean vote for thermal comfort, this study aimed to determine the corresponding air supply conditions for mixing and displacement ventilation systems under summer and winter conditions. The results show that it is possible to find the optimal air supply conditions in fewer than 10 design cycles if the initial conditions for design variables are provided within a reasonable range. This design method has a high computing efficiency as it takes one hour for a design cycle using a 16-core cluster. In addition, the results show that a displacement ventilation system provides a better thermal comfort level than a mixing ventilation system.

Determination of the optimal control parameter range of air supply in an aircraft cabin

Comfortable and healthy aircraft cabin environment is required as more and more people choose to travel by air. The cabin environment is optimized by searching the optimal control parameters such as air supply velocity, angle and temperature. The optimal solutions are obtained by combining a multi-objective particle swarm optimization (MOPSO) with the simulation of computational fluid dynamics (CFD). It is found that different combinations of optimal air supply parameters can build an optimal cabin environment and the locations of the obtained optimal solutions are isolated in their value spaces. To achieve a stable engineering control operation, the determination of a stable range of optimal air supply parameters is required. Therefore, a method by using cluster analysis is developed to obtain stable ranges of optimal air supply parameters. Results show that the proposed method can obtain the ranges of optimal air supply parameters successfully.

Optimization of air supply location, size, and parameters in enclosed environments using a computational fluid dynamics-based adjoint method

Optimal design of an indoor environment based on specific design objectives requires a determination of thermo-fluid control methods. The control methods include the air supply location, size, and parameters. This study used a computational fluid dynamics- (CFD) based adjoint method to identify the optimal air supply location, size, and parameters. Through defining the air distribution in a certain area (design domain) as a design objective in a two-dimensional, ventilated cavity, the adjoint method can identify the air supply location, size, and parameters. However, the air supply location, size, and parameters were not unique, which implied multiple solutions. By using any of the air supply location, size, and parameters identified as boundary conditions for forward CFD simulations, the computed air distribution in the design domain was the same as that used as a design objective. Thus, the computing costs did not depend on the number of design variables.

Inverse design of aircraft cabin environment by coupling artificial neural network and genetic algorithm

An inverse design method is proposed to achieve the pre-set control objectives of the aircraft cabin environment. The method combines the artificial neural network and the genetic algorithm, and the training and testing data of the artificial neural network is obtained by computational fluid dynamics analysis. Both of the thermal comfort and energy consumption are considered in the inverse design. The artificial neural network is used to identify the relationship between the thermal comfort and the air supply parameters (inlet velocity magnitude and angle, inlet air temperature). The genetic algorithm coupled with the well-trained artificial neural network is used to design the aircraft cabin environment. Numerical results show that the Bayesian regularization algorithm is proved to have better generalization capability than the other training algorithms for the artificial neural network. The increase of training data quantity improves the generalization capability of the artificial neural network, while it spends more simulation time. A computational fluid dynamics database with 60 datasets is shown to be suitable to the present inverse design, and the testing error of the artificial neural network is below 8.2%. Several groups of optimal air supply parameters are found with different trade-offs between the thermal comfort and energy consumption. The best solution of thermal comfort, i.e., the percentage of zone with |PMV| >0.5 in all cabin control domains, is less than 7.8%.

Optimal air distribution design in enclosed spaces using an adjoint method

This investigation studied an adjoint method to achieve the optimal design of ventilation in an enclosed environment and validated it with two, two-dimensional cases. A part of the flow field and/or temperature field was defined as the design objective, and the thermo-fluid boundary conditions were determined as the design variables. By using the adjoint method together with a steepest descent method that was implemented in OpenFOAM, this investigation found the optimal air supply parameters. With the determined air supply parameters, this study used Computational Fluid Dynamics to calculate the flow and/or temperature fields, which are in a good agreement with the design objective. However, as the adjoint method could only find the local optima, the calculations with different initial inlet air conditions may lead to multiple optimal solutions. This is common with the gradient-based method.

English

A wide range of air supply parameters is needed for the flueric actuators testing in order to find their optimum working regime. A system for conditioning these parameters, namely pressure, temperature, mass and volume flow rate has been built for this purpose. The measured values are continuously stored on the PC hard drive and are checked automatically for keeping them in the normal operating range. In case any of them are going out of this range, this system warns the operator and performs automatic actions for limiting or partially or totally shutting down the system.

Development of a Biomass-Fired Combustion Unit for Residential Heating

An innovative combustion unit was designed and implemented, aiming at the production of thermal energy, using different types of biomass fuels. The unit was made out of conventional materials, had a nominal capacity of 65 kWth and comprised a silo, a continuous feedstock supply system, a desiccator, a cutting mill, and a cross flow boiler. Among the two residues tested, olive kernels produced a higher thermal efficiency and lower CO, SO2, and NOx emissions. A series of experiments, conducted at different biomass/air feed rates, showed that at a feedstock mass flow of 14.4 kg/h improved combustion conditions and heat recovery were obtained. Gaseous emissions were kept below the threshold limits and system efficiency was 81.3%. The unit needs to be optimized in terms of air supply and optimal parameters control systems.

Influence of air supply parameters on indoor air diffusion

This paper presents the field distributions of air velocity, temperature, contaminant concentration, and thermal comfort in an office with displacement ventilation for different air supply parameters such as the effective area, shape, and dimension of the diffuser and the turbulence intensity, flow rate, and temperature of the air supplied. The research is conducted numerically by using an airflow computer program based on a low-Reynolds-number k- ϵ model of turbulence. It can be concluded that the effective area, shape, and dimension of the diffuser and the turbulence intensity of the air supplied have little effect on the room air diffusion except at floor level. The influence of the flow rate and temperature of the air supplied is very significant on the air diffusion as well as on the thermal comfort and indoor air quality.