Multiple regression analysis is a statistical technique which allows to predict a dependent variable from more than one independent
variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is
applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for
four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change
rates 3–6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and
local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple
stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly
influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the
local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.
[1]
L. L. Christianson,et al.
Characteristics of diffuser air jets and airflow in the occupied regions of mechanically ventilated rooms - a literature review
,
1993
.
[2]
J. Elashoff,et al.
Multiple Regression in Behavioral Research.
,
1975
.
[3]
Christopher H. Achen.
Interpreting and Using Regression
,
1982
.
[4]
Eric R. Ziegel,et al.
Data Mining Cookbook
,
2002,
Technometrics.
[5]
H. Awbi.
Ventilation of buildings
,
1873
.
[6]
Youngjun Cho,et al.
The variation of ventilation performance in relation to change in workstation location in a ventilated room
,
2003
.