Flow Boiling Characteristics and Active Control of Refrigerant Cooling Systems

  • Jianwei Gao

Student thesis: Master's Thesis

Abstract

In flow boiling systems, heat flux to wall superheat relation tells a hysteresis phenomenon. In this relation, critical heat flux (CHF) and critical rewetting heat flux (CRHF) determine when the hysteresis happen and to what extent it will be. One of the correlations in previous papers is applied to determine CHF and dryout point. To predict CRHF, the axial heat conduction is considered, since it is one reason that leads to flow boiling hysteresis. Then, separatedflow model is proposed to carry out this method, and the result shows that CRHF well agrees with experimental one. Besides, wall temperature dynamic process is shown, and the transition fastness is analyzed. To make totally rewetting fast occur in the flow boiling system, MPC theory is applied to optimize the mass flow rate. A control model is developed from the physical flow boiling system and MPC method is used to control the relative parameters, thus the dryout region can be avoid or fast removed. In practical control systems, system states need to be estimated when they are not measurable. In this work, we consider output feedback model predictive control (MPC) for linear parameter varying (LPV) systems with input constraints. We proposed two approaches to obtain the observer gain, that is to compute the gain in the dynamic optimization at each time instant (on-line), and to compute the gain in advance (off-line), respectively. By applying both approaches, the state estimation error goes to zero asymptotically, meanwhile, the state feedback gain is optimized. In fact, the on-line approach can help enlarge the feasibility region and improve the control performance. It has been shown that feasibility and stability of both approaches can be maintained for the closed-loop control systems even in the presence of state estimation error. Examples has shown the effectiveness of the proposed methods. This work investigates flow boiling system and MPC control, and combines these two topics together to develop a flow control system. The methodology can be applied in other engineering applications where control need to be combined.
Date of AwardMay 2015
Original languageAmerican English
SupervisorTJ Zhang (Supervisor)

Keywords

  • Cooling systems
  • Axial hear conduction
  • Flow Boiling system
  • Model Predictive control.

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