TY - JOUR
T1 - A study of transient wall plume and its application in the solution of inverse problems
AU - Bangian-Tabrizi, Ardeshir
AU - Jaluria, Yogesh
N1 - Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Inverse engineering problems have many applications in various industries. While most of the research is focused on the steady state problems, transient heat transfer also has potential with regard to application and research. A detailed study of the forward transient wall plume is developed and the analytical results are used to build an inverse solution methodology. The goal of the inverse solution is to find the heat source location and energy input or strength using a few, limited, data points downstream. The methodology involves developing interpolating functions that relates transient features to plume strength and location at each location downstream of the plume and then using these functions to set up a system of equations. This system of equations is then solved to find the unknown variables. A search based optimization method, particle swarm optimization (PSO), is used to find the optimal sensor locations downstream of the plume in order to minimize the number of downstream data points needed for an accurate prediction.
AB - Inverse engineering problems have many applications in various industries. While most of the research is focused on the steady state problems, transient heat transfer also has potential with regard to application and research. A detailed study of the forward transient wall plume is developed and the analytical results are used to build an inverse solution methodology. The goal of the inverse solution is to find the heat source location and energy input or strength using a few, limited, data points downstream. The methodology involves developing interpolating functions that relates transient features to plume strength and location at each location downstream of the plume and then using these functions to set up a system of equations. This system of equations is then solved to find the unknown variables. A search based optimization method, particle swarm optimization (PSO), is used to find the optimal sensor locations downstream of the plume in order to minimize the number of downstream data points needed for an accurate prediction.
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U2 - 10.1080/10407782.2019.1580958
DO - 10.1080/10407782.2019.1580958
M3 - Article
AN - SCOPUS:85063085662
SN - 1040-7782
VL - 75
SP - 149
EP - 166
JO - Numerical Heat Transfer; Part A: Applications
JF - Numerical Heat Transfer; Part A: Applications
IS - 3
ER -