Abstract
Introduced in this article is a 1:15 brine model experiment rig with an actual large space building as the research object, which provides different concentration brine for a simulation of the stratified air conditioning in the steady-state flow field featured with columnar air supply in the bottom, heat source on the ground, the central air return, and air exhaust from roof in a large space. According to the similarity theory, it is concluded that the similarity criterion numbers applied here are Reynolds number (Re) and Archimedes number (Ar) for designation of experiment rig size, choosing device type, and confirming experiment condition. In the designation of key components of experiment rig, the application of automation control makes brine recovery and recycling in the process; designation of electrical control system makes a centralized control of experiment start–stop and the adjustment of the pipeline flow, realizing automation in the whole experiment process. Particle image velocimetry testing technology is used to get velocity vector field of air return mouth area in the model under various working conditions, and also proper orthogonal decomposition method is applied to analyze flow field structure of air return mouth area and reconstruct it. Consequently, we can get a kinetic energy ratio of return air entrainment of lower air-conditioning section and upper non-air-conditioning section in large space. Experiments show that under the conditions of same air supply, indoor environment temperature difference, and height and direction of return air inlet, fastening the speed of return air suction, the entrainment of flow field around it strengthens accordingly. The entrainment of return air inlet has more kinetic energy in the lower air-conditioning section than the upper non-air-conditioning section.
Highlights
In order to create a more comfortable and energysaving indoor thermal environment, the stratified air-conditioning mode with downside air supply is increasingly applied to large space building
The upper and lower of the 20 3 120 areas have a relatively minimum kinetic energy ratio (66.15%), which is due to the chosen area border near the rising plume and the increase in kinetic energy because of the lower regional velocity field by plume disturbance
The proportion of the kinetic energy calculated in the selection of Particle image velocimetry (PIV) shooting area within this period can reflect kinetic energy of upper and lower areas of the return air entrainment stratification plane
Summary
In order to create a more comfortable and energysaving indoor thermal environment, the stratified air-conditioning mode with downside air supply is increasingly applied to large space building. Testing table is set up with five pipes of simulations are water supply, water return, and water tion of under-floor air supply, middle air return, density, which are determined by supply and air exhaust from the top, heat source on the return air parameters of the air-conditioning bottom, and the fresh and return air mixed, system in the actual working condition, and the making electromagnetic flowmeter, inverter, density of the main water tank is determined by and water pump as a closed-loop control system average temperature state of ordinary section in in the pipeline; before operation of experiment, actual working condition. If the density of the main water tank is set verter, when running experiments; in the operaaccording to 38° which is higher than the airtion of experiment, electromagnetic flowmeter conditioning designed temperature (e.g. 27°), it transmits the digital signal-measured flow rate equals to indoor internal heat source for the tank value to the inverter and PID algorithm of bottom-air-conditioning area. Suppose you have X instantaneous velocity vector field, and each velocity vector field can be used as a x1 X x2 two-dimensional matrix V, while the element value Vmn in matrix is represented the location of the flow field parameters, indicating the correlation of X instantaneous flow field elements covariance matrix of AX X X is expressed as
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