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research-article

ENERGY-ORIENTED MODELING AND OPTIMIZATION OF A HEAT TREATING FURNACE

[+] Author and Article Information
Vincent R. Heng

McKetta Department of Chemical Engineering University of Texas at Austin Austin, TX 78712
vincent.heng@utexas.edu

Hari S. Ganesh

McKetta Department of Chemical Engineering University of Texas at Austin Austin, TX 78712
hariganesh@utexas.edu

Austin R. Dulaney

McKetta Department of Chemical Engineering University of Texas at Austin Austin, TX 78712
austindulaney@utexas.edu

Andrew Kurzawski

Department of Mechanical Engineering University of Texas at Austin Austin, TX 78712
andrew.kurzawski@utexas.edu

Michael Baldea

McKetta Department of Chemical Engineering, Institute for Computational Engineering and Sciences The University of Texas at Austin Austin, TX 78712
mbaldea@che.utexas.edu

Ofodike A. Ezekoye

Department of Mechanical Engineering The University of Texas at Austin Austin, TX 78712
dezekoye@mail.utexas.edu

Thomas F. Edgar

McKetta Department of Chemical Engineering, Energy Insititute The University of Texas at Austin Austin, TX 78712
tfedgar@austin.utexas.edu

1Corresponding author.

ASME doi:10.1115/1.4035460 History: Received January 11, 2016; Revised December 09, 2016

Abstract

In this paper, we develop an energy-focused model of an industrial roller hearth heat treating furnace. The model represents radiation heat transfer with non-participating gas and convective heat transfer. The model computes the exit temperature profile of the treated steel parts and the energy consumption and efficiency of the furnace. We propose a dual iterative numerical scheme to solve the conservation equations and validate its efficacy by simulating the dynamics of the furnace during startup, as well as for steady-state operation. A case study investigates energy consumption within the furnace under temperature control. We first consider a heuristic control strategy using simple linear controllers. A response surface approach is then used to find the optimal set points which minimize energy consumption while ensuring desired part temperature properties are met when processing is complete. With optimized set points, 4.8% less energy per part is required versus the heuristic set points.

Copyright (c) 2016 by ASME
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