We describe an analog CMOS VLSI system that can process real-time signals from integrated shear stress sensors to detect regions of high shear stress along a surface in an airflow. The outputs of the CMOS circuit control the actuation of integrated micromachined flaps with the goal of reducing this high shear stress on the surface and thereby lowering the total drag. We have designed, fabricated, and tested components of this system in a wind tunnel in both laminar and turbulent flow regimes with the goal of building a wafer-scale system

Fukang, Jiang

Goodman, Rodney

Gupta, Bhusan

Ho, Chih-Ming

Tai, Yu-Chong

Tsao, Tom

Tung, Steve

Caltech Authors - Main

A Wafer-Sca e MEMS & Analog VLSI System for Active 
Drag Reduction 
Bhusan Gupta, Rodney Goodman, Fukang Jiang, Tom Tsao, Yu-Chong Tai 
Dept. of Electrical Engineering 
California Institute of Technology 
Pasadena, CA 9 1 125 
Steve Tung, Chih-Ming Ho 
MANE 
UCLA 
Los Angeles CA 90024 
E-mail: bguptac3caltech. edu 
Abstract 
We describe an analog CMOS VLSI system that can process real-time signals from 
integrated shear stress sensors to detect regions of high shear stress along a surface in an 
airflow. The outputs of the CMOS circuit control the actuation of integrated micromachined 
flaps with the goal of reducing this high shear stress on the surface and thereby lowering the 
total drag. We have designed, fabricated, and tested components of this system in a wind 
tunnel in both laminar and turbulent flow regimes with the goal of building a wafer-scale 
system. 
1 : Introduction 
In today's cost-conscious air transportation industry, fuel costs are a substantial economic 
concern. Drag reduction is an important way to increase fuel efficiency which reduces these 
costs. It is estimated that even a 5% reduction in drag can easily translate into savings of 
millions of dollars in annual fuel costs. 
Counter-rotating vortic Flow into page 
Region of high shear q t r e q a  
Figure 1 Diagram showing the interaction of a vortex pair and the wall illustrating the 
high shear stress (hence drag) region created by the pair of counter-rotating streamwise 
vortices. 
Organized structures which play an important role in turbulence transport may cause large 
skin friction drag. Commonly observed near-wall streamwise vortices cause high drag in 
turbulent flows (Figure 1). The interaction of these vortices, which appear randomly in both 
space and time, with the viscous layer near a surface creates regions of high surface shear 
stress. This shear stress, when integrated over a surface, contributes to the total drag. 
Attempts to reduce drag by controlling turbulent flows have focused on methods of either 
preventing the formation or mitigating the strength of these vortices. The microscopic size of 
46 0-7803-3639-9196 $4.00 01996 E E E  
Session 4: MEMS and Sensors 47 
these vortices, which decreases as the Reynolds number of the flow increases, has limited 
physical experimentation, and the inherent complexity of the non-linear Navier-Stokes 
equations has likewise limited the analytical approaches. 
2: How Small Is Small? 
By examining shear stress patterns in our wind tunnel at velocities between 10 and 20 m/s, 
one can narrow the scope of the problem in order to extract useable statistics. The drag- 
inducing vortex pair streaks vary as the Reynolds number of the flow changes. For a typical 
airflow of 15 meters per second (54 km/hr) in the wind tunnel, the Reynolds number is about 
lo4. This, in turn, gives the vortex streaks a statistical mean width of about 1 millimeter. The 
length of a typical vortex streak can be about 2 centimeters giving the streaks a twenty to one 
aspect ratio. The average spacing between streaks is about 2.5 millimeters. The mean rate of 
appearance of the streaks is approximately 100 Hz. The appearance and disappearance of 
these vortex pairs can be best be described by a chaotic process. 
3: Computer simulations 
Counter-rotating vorti Flow into pag, 
10 
Surface 
Actuation = -+lo) 
Figure 2 Simple control law which demonstrates the required actuation at the wall 
boundary to achieve a significant drag reduction. 
Numerical simulations demonstrate that suppressing the interaction between stream-wise 
vortices and the wall [ I ]  achieves significant drag reduction (on the order of about 25%). 
These computational fluid dynamics' experiments incorporate active feedback control to 
achieve this goal. 
The control scheme used in the experiments involved blowing and suction at the wall 
according to the normal component of the velocity field. This normal component is sensed in 
the near-wall region away from the surface (see Figure 2). It appears that a simple control law 
that pushes the areas of high shear stress away from the wall is beneficial to minimizing the 
overall drag. This observation forms the basis for the system that we wish to build. 
4: System Details 
We want to combine the technologies of silicon micromachining and analog VLSI to build 
an integrated wafer-scale system which actively strives to reduce the drag along its surface. 
Micromachining technology allows construction of fluid sensors and actuators on the same 
scale as the vortex pairs. Analog VLSI affords us the ability to build dense circuits which do 
the real-time processing necessary for an integrated system. 
48 1996 Innovative Systems in Silicon Conference 
Figure 3 Schematic diagram of our proposed system. 
The goal is to design a system (Figure 3) that incorporates VLSI control circuitry along 
with microscopic sensors and actuators and control circuitry that can actively deform its 
surface to reduce drag. 
Circuits process the signals from the sensors to find regions of high shear stress. This 
detection process uses information about the spatial and temporal nature of the streaks. First, 
the long and narrow aspect ratio leads to building “column”-oriented templates for streak 
detection. We organize the sensor outputs into thin feature detectors oriented in the direction 
of the airflow. When several sensors in a column register either a larger or smaller output than 
their neighbors in a spanwise direction, this difference accumulates. If this accumulated 
difference exceeds a threshold, a vortex pair streak may be present in that column. The 
appropriate control action raises the associated actuator. 
5: Micromachined Components 
Silicon micromachining technology is utilized to build the microsensors and microactuators 
[2,3,4]. The details of the sensors and actuators are covered elsewhere but are briefly included 
here for completeness. 
5.1: Shear Stress Sensor: 
Figure 4 Shear stress sensor showing the polysilicon transducer element over the silicon 
nitride diaphragm. 
The microsensor (Figure 4) allows measurement of the heat transfer between a heated wire 
and the air. Heat transfers by convection from the electrically heated wire to the fluid flow 
causing a power change in the polysilicon wire. The sensors used in this experiment have 
been fabricated as a single row of 25 sensors. This allows continuous monitoring of a 
spanwise section of the wind tunnel. This sensor allows us, for the first time, to record the 
instantaneous shear stress associated with the near wall structures. 
Session 4: MEMS and Sensors 49 
Figure 5 Array of 25 shear stress sensors which span a distance of 7.5mm. 
5.2: Microactuator: 
The microactuator (Figure 6) [ 5 ]  is a thin plate that is raised via both magnetic and thermal 
actuation. Current through the coil of metal on the flap interacts with an external magnetic 
field to cause up to a 1 OOpm vertical deflection. 
Figure 6 Photograph of a microactuator and an array of microactuators. The actuator 
measures about 300pn by 500pm. 
5.3 Wafer Integration 
Our goal is to build a completely integrated system so the fabrication processing for both 
the shear stress sensor and microactuator is chosen to be compatible with the CMOS circuitry. 
We intersperse the micromachining steps with the CMOS process steps so that we do not 
impair either part. Because of the complexity involved in this system, we split the process 
flow among two different fabrication facilities. The 2.0pm double polysilicon CMOS 
processing is done in the Microlab at the University of California at Berkeley. The 
micromachining processing is carried out at the fabrication facility at Caltech. 
The wafers start out at Berkeley with the first sixteen steps of the CMOS process up to 
metalization. The wafers then come to Caltech for the first round of micromachining steps 
primarily centered around the sensor. For instance, the nitride which is used as the sensor 
diaphragm material has to be deposited before the CMOS aluminum otherwise the high 
temperature would cause the aluminum to melt. The wafers then go back to Berkeley for 
metalization. The wafers then come back to Caltech for the actuator processing. This is the 
last set of processing steps because the actuator requires a release step which then makes any 
further processing difficult. The combined process flow requires about 32 masks and over 65 
different processing steps. The overall process has four polysilicon and five metal layers. 
50 1996 Innovative Systems in Silicon Conference 
6: Control Circuit 
Activity 
Threshold Unit Yl Actuator 
Figure 7 Block diagram of the complete detectionkontrol architecture. 
Figure 7 shows a diagram of how the information is processed in the detectiodcontrol chip. 
A non-linear filtering network connects together the amplified outputs of the shear stress 
sensors. The filtering preserves large differences between adjacent sensors while smoothing 
small differences. The comparison and aggregation is organized by columns corresponding to 
different actuators. Once the signal is aggregated and exceeds a threshold then the actuator is 
driven. The general design methodology for the circuits is described in [6]. 
7: Prior Results 
We have built previous versions of the system that use separate substrates for the sensor, 
control circuitry, and actuator. In this discrete system, we have been able to check the 
functionality and performance of our design. Figure 8 plots the response from the control 
circuitry versus the measured instantaneous shear stress. The plot demonstrates that the large 
shear stress values trigger the actuator. Figure 9 shows a plot of the full 25 sensor field and 
the reduced five-sensor field used to generate the detectiodcontrol output. 
8: Wafer Scale System 
We expect to have results of our wafer-scale system soon. The wafer consists of the same 
die replicated many times (Figure 10). The die contains both the sensors, actuators, and VLSI 
control circuih-y. 
Session 4: MEMS and Sensors 51 
Channel 1 
Channel 2 
I 
Figure 8 Transfer curve for three channels of the prior dctection/control chip with the 
data recorded at  15 m/s. The data indicates that for large values of shear stress, the 
detection and control circuitry would, in fact, turn on an actuator. 
Figure 9 Two dimensional flow picture of instantaneous shear stress. From left to right 
we plot the full span (25 sensor) recording, an enlargement of the middle three sensors, 
and finally, the output of the detection/control chip corresponding to those three inputs. 
We record the data in a turbulent flow regime with a free stream velocity of 10 m/s. We 
obtain the two dimensional aspect of the plots by time sampling a one dimensional span. 
The lighter greyscale values correspond to higher values. 
52 1996 Innovative Systems in Silicon Conference 
h 
Mi 
C’ 
Aicro 
cro SI 
ontrol 
Actuators 
m o r s  1 
Circuitry 
Figure 10 Plot of one die of a wafer-scale implementation 
Acknowledgments: 
This work is supported in part by the Center for Neuromorphic Systems Engineenng as a part of the National Science Foundation 
Engineering Research Center hogram under grant EEC-9402726, and by the California Trade and Commerce Agency, Office of Strategic 
Technology under gant C94-0165 This work 1s also supported in part by ARPAIONR under grant no NO0014 93-1-0990, and by an 
AFOSR University Research Initiative grant no F49620-93-1-0332 
References 
[I] P Mom, J Kim, H Choi, “On Active Control of Wall-Bounded Turbulent Flows,” AIAA Paper No 89-0960, 1989 
[Z] P R Bandyopadhyah, “Development of a Microfabricated Surface for Turbulence Diagnostics and Control,” ASME 
Application of Microfabricaiion to Flurd Mechanics, Chicago (1994), pp 61-14 
[3] C Liu, Y C Tai, J B Huang, C M Ho, “Surface Micromachined Thermal Shear Stress Sensor,” ASME Application of 
Microfabrication io FluidMechanrcs, Chicago (1994), pp 9-15 
[4] F Jiang, Y C Tat, J B Huang, C M Ho, “Polysilicon Structures for Shear Stress Sensors,” to be published in Tech 
Digest IEEE TENCON 95, Hong Kong, Nov 1995 
[5] T Tsao, C Lm, Y C Tal, C M Ho, Micromachined Magnetic Actuator for Active Fluid Control,” ASME Application of 
Microfabrication to Fluid Mechanics, Chicago (1994), pp 31-38 
[6] C A Mead, Analog VLSI and Neural Systems, Addison-Wesley, Reading, Massachusetts (1 989) 


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A wafer-scale MEMS and analog VLSI system for active drag reduction

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A wafer-scale MEMS and analog VLSI system for active drag reduction

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