Thermal-fluid Dynamic Systems

Actuators & Sensors

Machine Vision

Robotics & Automation

Thermal-fluid Systems

Magnetic Systems

Compliant Systems

Biomechatronics

The following are some selected applications to help illustrate physics based models for control of thermal fluid dynamic systems.

Optical Fiber Drawing (Finite Deference Methods)

Optical fibers are essentially the hardware backbones of the information superhighway. The interests to improve productivity and reduce cost in the late 1990s have motivated manufacturers to use larger diameter preforms and higher draw speeds. The trade-off, however, is that the glass takes a longer (unknown) distance to cool into a fiber after leaving the furnace, for which an insulated post-chamber is added to gradually cool the fiber to solidification in order to reduce optical losses in the final product. Traditional  1D approximation and control methods with assumptions made for drawing small-diameter performs  (that simply relied on manipulating the draw speed) are no longer adequate.

This fiber draw process is an excellent example, which involves practically all modes of flow/heat transfer and glass is a participating media in radiation. Exceptionally stringent production requirements, along with the difficulties in making precise measurements in the furnace domain, have posed a significant challenge in the design/control of a modern draw process. The problem becomes one of multivariable distributed temperature/ free-surface flow control.  

Motivated by the needs for a method to derive practical, physical-based dynamic models that capture the essential characteristics for precision diameter control of an optical fiber draw process, this research focused on developing several thermal-fluid models, simulation methods and model reduction for design/control of a modern draw tower:

• Radiative heat transfer problems in optical fiber manufacturing [1-2]

• Computational issues in modeling of free-surface flow for high-speed drawing from large-preforms [3]

• Distributed parameter models characterizing a free surface flow coupled with the dominant radiative transfer and mixed air convection cooling for the design and control of modern optical fiber draw processes [4]

• Extended (in their second paper) the Karhunen-Loeve decomposition technique with a Galerkin procedure to derive a reduced-order model (ROM) for the multi-variable distributed-parameter precision controlled system [5]

The above collection offers several different levels of models which can be applied to design optimization, dynamic analysis, performance prediction, and real-time control of a modern draw tower; thereby offering an effective means to reduce time and costly experiments in developing and implementing model-based control systems. While these models have an immediate application in optical glass fiber drawing, these modeling techniques presented in this collection of papers are applicable to thermal processing of other materials, including baking and microwave pre-cooking of food products.

Modeling and Control of Space Electronic Cooling Systems

Recent advances in the microelectromechanical (MEMS) systems fabrication technology with increased computing power, along with the interest to reduce size, power consumption, and fabrication cost, have resulted in a number of emerging space mechatronics such as nano-satellites that have the potential of revolutionizing the space industry and help achieve ambitious missions. Space radiators play an important role in dissipating heat generated to its environment; the transfer process is dominated by the heat radiation at the radiator surface. Because of their large power density and small available surface area for radiation, Space electronics are subject to a relatively stiff heat-dissipating task.  References [6-8] report a few research findings (in collaboration with Beihang University) on thermal management, dynamic analysis and fuzzy-logic-based control methods for cooling spacecraft electronics space:

• Paper [6] presents the  concept and working principle of an equivalent physical simulator designed for ground simulation of a nano-satellite space-radiator.

• Transient performance analyses are essential for the successful design of a spacecraft thermal management system.  Papers [6-7] present dynamic models for analyzing and controlling system level transient responses of thermal management systems employing MEMS technologies.

Immersion lithography

One of the main factors driving the improvements in complexity and cost of ICs is improvements in photolithography and the resulting ability to print ever smaller features. Immersion lithography improves optical resolution to 45 nm and below without much change in technical infrastructure. To increase the refraction index in the space between the projection lens and substrate, liquid with high refractive index must be confined by an immersion unit within the gap while the wafer moves at high speeds. Motivated by the interest to increase production throughputs in semiconductor industry, wafers are scanned at higher and higher velocity and acceleration. The meniscus stability depends on the scan speed, the viscosity and surface tension of the liquid, the contact angles on the resist side and the immersion unit side, as well as the dynamics of the liquid in the gap between the last lens and wafer. To maximize the critical scan speed of an immersion scanner, a  good understanding of the fluid dynamics in the gap between the  lens and substrate is desired. With experiments conducted at Zhejiang University, [9] presents a method for characterizing the meniscus dynamics using experimentally obtained images from two different (hydrophilic and hydrophobic) lens surfaces.

References:

1. Wei, Z. Y., K.-M. Lee, S. Tchikanda, Z. Zhou, and S.-P. Hong, "Effects of Radiative Transfer Modeling on Transient Temperature Distribution in Melting Glass Rod," ASMEJ. of Heat Transfer. August 2003, vol. 125, no. 4, pp. 635-643.

2. Wei, Z. Y., K.-M. Lee, Z. Zhou, and S.-P. Hong, "Modeling of Advanced Melting Zone for Manufacturing of Optical Fibers," ASME J. of Manufacturing Science and Engineering. November 2004, vol.126, issue 4, pp. 750-759.

3. Wei, Z. Y., K.-M. Lee, S. Tchikanda, Z. Zhou, and S.-P. Hong, "Free Surface Flow in High Speed Fiber Drawing with Large-diameter Glass Preforms," ASME J. of Heat Transfer. October 2004, vol. 126, no. 5, pp. 713-722.

4. Lee, K.-M., Z. Wei, Z. Zhou, and S.-P. Hong, "Computational Thermal Fluid Models for Design of a Modern Fiber Draw Process," IEEE Trans. on Automation Science and Engineering. January 2006, vol. 3, no. 1, pp. 108-118.

5. Lee, K.-M., Z. Wei, and Z. Zhou, "Modeling by Numerical Reduction of Modes for Multi-Variable Control of an Optical Fiber Draw Process," IEEE Trans. on Automation Science and Engineering. January 2006, vol. 3, no. 1, pp. 119-130.

6. Li, Y. Z., K.-M. Lee, and J. Wang, "Analysis and Control of Equivalent Physical Simulator for Nanosatellite Space Radiator," IEEE/ASME Trans. on Mechatronics. Feb. 2010, vol. 15, no 1, pp. 79-87.

7. Li, Y.-Z. Y.-Y. Wang and K.-M. Lee, "Dynamic Modeling and Transient Performance Analysis of a LHP-MEMS Thermal Management System for Spacecraft Electronics," IEEE Trans. on Components and Packaging Technologies. Sept 2010, vol. 33, no. 3, pp. 597-606.

8. Li, Y. Z. and K.-M. Lee, "Thermohydraulic Dynamics and Fuzzy Coordination Control of a Microchannel Cooling Network for Space Electronics," IEEE Trans. on Industrial Electronics. Feb. 2011, vol. 58, issue. 2, pp. 700-708.

9. Chen, Y., K.-M. Lee, X. Fu, "Effect of Upper Surface Characteristics on Meniscus Stability in Immersion Flow Field," Microelectronic Engineering, 88 (2011) 1939–1943.02.045.