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Winter and summer thermal comfort and air flow measurements in a naturally ventilated room
Abstract
The objective of this research is to investigate thermal comfort and air flow distribution inside a test room that is naturally ventilated. The test room is situated in a relatively sheltered location and is ventilated through adjustable louvres. The air pressures and velocities across the openings together with indoor air temperature and velocity at four locations and six different levels are measured. The outside local temperature, wind velocity and direction are also monitored. The collected data are used to predict thermal comfort parameters across the test room. Tests were carried out over winter and summer times. The experimental results demonstrate that for both winter and summer the air was entering the test room at the bottom and leaving at the top louvre. The amount of air flow over the winter was increased as the heat input varied from 2 kW to 4 kW. The predicted thermal comfort indicated that PPD values (percentage of people dissatisfied) for summer are significantly improved with a higher temperature difference between inside and outside and higher wind velocity. Over the winter period with internal heat load of 4 kW the PPD values were improved by 40%.
... Examination of the above studies [31][32][33][34] suggests that a neural network analysis approach would be particularly appropriate for predicting the air distribution and air quality within a space at the early design stage. Given that enough data is available, any number of input/output variables can be used for the neural network analysis. ...
The major objective of this paper is to illustrate how neural network analysis techniques might play an important role in modeling, predicting, and estimating in building services engineering. The paper outlines an understanding of how neural networks operate by way of presenting a focused discussion and illustration of appropriate problems in the different disciplines of architectural and building acoustics, civil and structural engineering and architectural science to which neural network analyses have been applied. Results of these neural network procedures, some of which are presented in this paper, are testimony to the potential of neural networks as a design tool in many areas of endeavor, including building services engineering.
In this paper the design and validation process of a supervisory control for a single-sided naturally ventilated test room is described. The controller is based on fuzzy logic reasoning and sets of linguistic rules in the form of IF-THEN rules are used. The inputs to the controller are the outside wind speed, outside and inside temperatures. The output is the position of the opening. The basis of any fuzzy rule system is the inference engine responsible for the input's fuzzification, fuzzy processing of the rule base and defuzzification of the output. The choice of the inference engine, starting with the selection of input and output variables and their membership functions. Three rule bases of different complexity were developed and are presented and analysed here. Validation through simulation offers possibility of testing the controller under extreme conditions regardless of physical limitations of an experimental test cell. Simulations were performed for different typical levels of input parameters and also for extreme ctitious conditions. Simulations were carefully designed to allow simultaneous comparison of different controllers' performances. Simulation results have shown that all three controllers are capable of responding to the changes in outside conditions by adjusting the opening positions. They satisfy security requirements due to strong wind and successfully, in a stable manner respond to sudden changes in wind velocity and outdoor temperature. A controller with more membership functions and therefore a larger number of IF-THEN rules was more responsive to the changes in outside conditions.
The objective of this research is to compare calculated and measured air flow distributions inside a test room which is naturally ventilated. The test room is situated in a relatively sheltered location and to visualise the resultant local wind pattern around the room for all prevailing wind directions wind tunnel trials were carried out. Both the wind tunnel and full-scale measurements show that the wind direction at the test cell was generally restricted to either a westerly or an easterly direction. To investigate air flow inside the room, the air pressures and velocities across the openings together with indoor air temperature and velocity at four locations and six different levels are measured. The experimental results demonstrate that for both winter and summer the air was entering the test room at bottom and leaving at the top louvre. Separate air flow and thermal modelling programs are used to predict the spatial distribution of the air flow and thermal comfort. The air flow distribution was predicted using a network air flow program. The predicted flow showed similar trends and the simulation results were in an agreement with the measured data. An explicit finite-difference thermal modelling simulation package was used to predict the thermal comfort indices.
This paper investigates air movements and temperature distribusions inside an office which is naturally ventilated. An existing environmental chamber with a volume of approximately 45 m3 is used to represent an office. The outside air is supplied into the environmental chamber through three different supply positions on the wall. Measurements of air temperature and velocity are carried out in the environmental chamber at different heights and positions in the chamber. The internal wall surface temperatures and outside air temperature are also monitored. The mean air velocity is measured at the same points as the air temperatures using omnidirectional anemometers. The outputs from the anemometers are fed into a microcomputer; these data are analysed for comfort using the predicted percentage of dissatisfaction (PPD) method of Fanger's thermal comfort criterion.
A major problem in the design of naturally ventilated buildings is the complicated interaction between the flow rates and the indoor air temperatures. The natural ventilation flow rates are influenced by the indoor air temperatures while the indoor air temperatures are in turn influenced by the flow rates. A good design tool should therefore consist of a flow model to determine the flow rates and a thermal to determine the indoor air temperatures. These two should be solved simultaneously in an integrated manner. Existing design tools lack the ability to address this.This paper describes the implementation and verification of the new flow model derived in Part 1 of this paper into such an integrated natural ventilation design tool. The thermal model is based on existing theory that has been verified extensively. An iterative solution algorithm is employed to ensure simultaneous solution of these two models.Continuous tracer gas and temperature measurements show that the integrated tool can be used with confidence in the design of naturally ventilated buildings. A case study is also presented that illustrates how the new tool can be used successfully to optimize the design of a naturally ventilated factory building.
Thermal comfort in a naturally ventilated test room is investigated. The test room is a lightweight portable cabin located in a sheltered area at Loughborough University, UK. Thermal comfort simulations were carried out for various sizes of openings and glazing. Medium and high thermal mass were added to the test room and their effects on thermal comfort were investigated. The results suggested that thermal mass has significant effect on thermal comfort parameters. Adding a 200 mm thick layer of medium-density concrete to the walls improved the thermal comfort over the summer by 40%.
In many cases natural ventilation may be sufficient to ensure acceptable comfort levels in occupied buildings. In these cases installation of energy-intensive active environmental control systems will not be necessary. This will result in considerable energy and cost savings and also indirectly in a reduced burden on the environment, since the use of energy is always associated with the production of waste materials.This paper describes the development of a new model to predict natural ventilation flow rates in buildings. The model employs a flow network where openings are represented by non-linear flow resistances. It accounts for both wind-induced pressures and pressures due to thermal forces. The model draws on a healthy balance between purely theoretical equations and empirical data. Simplified equations are derived through a synthesis of measured data obtained in boundary layer wind tunnel tests as well as from the literature. Tracer gas measurements show a good comparison between measured and predicted ventilation rates.The implementation of the new model into an integrated design tool for naturally ventilated buildings is discussed in Part 2 of this paper.