structural dynamics & vibration control lab 1 smart passive system based on mr damper for...

Structural Dynamics & Vibration Control LabStructural Dynamics & Vibration Control Lab 11

Smart Passive System based on MR DamperSmart Passive System based on MR Damperfor Benchmark Structural Control Problemfor Benchmark Structural Control Problemfor a Seismically Excited Highway Bridgefor a Seismically Excited Highway Bridge

4th World Conference on Structural Control and Monitoring

Kang-Min Choi, KAIST, KoreaHyung-Jo Jung, Sejong University, KoreaSang-Won Cho, The University of Western Ontario, CanadaIn-Won Lee, KAIST, Korea


CONTENTS CONTENTS

I.I. IntroductionIntroduction

II.II. Benchmark Highway Bridge StructureBenchmark Highway Bridge Structure

III.III. Smart Passive Control SystemSmart Passive Control System

IV.IV. Numerical Simulation ResultsNumerical Simulation Results

V.V. ConclusionsConclusions

Contents


- Viscous fluid out of magnetic field

- Solid-like in a magnetic field

- Proportional strength to magnitude of magnetism

Magnetorheological (MR) fluid

IntroductionIntroduction Semiactive MR Dampers

Introduction

Without Magnetic FieldsWithout Magnetic Fields With Magnetic FieldsWith Magnetic Fields


- Damping coefficient depending on electric current

- Requirements : External power for current supply

Sensors for feedback control

MR fluid damper

Introduction

Limitation for large-scale structuresLimitation for large-scale structures


Introduction

Cho, S.W., Jung, H.J., Lee, I.W. (2005) “Smart passive syste

m based on magnetorheological damper.”

Smart Materials and Structures, 14, 707-714.

- Change characteristics of MR damper

with electromagnetic induction (EMI) system

- Control without external power and control algorithm

- Verified by small-scaled shaking table experiment(Jung et al. 2005)

Smart Passive Control System


Introduction

Investigate the effectiveness of the Smart Passive

Control System for Benchmark Structural Control

Problem for a Seismically Excited Highway Bridge

Objective of this study:


91/5 highway bridge in southern California, USA

- Details of the bridge are presented in the definition paper (Agrawal et al. 2005)

Benchmark Highway Bridge StructureBenchmark Highway Bridge Structure

Structural Model

Benchmark Highway Bridge Structure

Isolated using four non-linear LRB on each abutment and one bearing on each bent column at the center


Benchmark Highway Bridge Structure

LRBMR damperEMI system

Smart Passive SystemSmart Passive System



Faster MR damper movement Higher EMF

EMI system is a source of power supply and has adaptability.

MR Damper

damper deformation

magnetic field

inducedcurrent

EMI system

Schematic of the Smart Passive System

Smart Passive Control SystemSmart Passive Control System


Faraday’s law of electromagnetic induction

EMI System for MR Damper


dt

dABN

dtN BdΦ

: Electromotive force (EMF)

N : Number of turns of coil

: Magnetic flux

B : Magnetic field

A : Area of cross section

BΦ

(1)



Magnetic Field

Solenoid

Movementof Solenoid

Change of Area

x

w

dt

dxwBN

dt

dABN

wBNK emf

(2)


Numerical Simulation ResultsNumerical Simulation Results

MR damper

Numerical Simulation Results

Maximum force level: 1000 kN

Maximum voltage : 10 Volts

- Parameters of the MR damper are described in the sample control design of the benchmark definition paper (Agrawal et al. 2005)


Input earthquakes

: North Palm Springs (1986)

: TCU084 component of Chi-Chi earthquake, Taiwan (1999)

: El Centro component of Imperial Valley earthquake (1940)

: Rinaldi component of Northridge earthquake (1994)

: Bolu component of Duzce, Turkey (1999)

: Nishi-Akashi component of Kobe (1995)



Evaluation criteria


J1: Pk. base shear

J2: Pk. over. mom.

J3: Pk. mid. disp.

J4: Pk. mid. acc.

J5: Pk. bear. Def.

J6: Pk. ductility

Peak response quantities Normed response quantities

J9: Norm. base shear

J10: Norm. over. mom.

J11: Norm. mid. disp.

J12: Norm. mid. acc.

J13: Norm. bear. Def.

J14: Norm. ductility



Controller itself

J15: Pk. control force

J16: Pk. Stroke

J17: Pk. instantaneous power

J18: Pk. total power

J19: Number of control devices

J20: Number of sensors

J21: Dim. of the discrete state vector


Optimal passive control


0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10

Optimal passive-on (5 V)

VVopt 5

Voltage (V)

Average of sum of evaluation criteria


Design of EMI system


0.6

0.7

0.8

0.9

12.5 25 37.5 50 67.5 75 87.5 100

)sec/( mVK emf

Design of EMI system (50V·sec/m)

mVK emf sec/50

Average of sum of evaluation criteria



- Number of turns of coil- Number of turns of coil - Magnitude of magnetic field

- Width of magnets

- Magnitude of magnetic field

- Width of magnets

TB 5.0

cmw 5

2000N

mVK emf sec/ 50

cmw 5

)( wBNK emf


Numerical results


0.00

0.60

1.20

1.80

2.40

J1 J2 J3 J4 J5 J6 J9 J10 J11 J12 J13 J14 J15 J16

Passive-off

Passive-on

Optimal passive

Lyapunov

Smart passive

- The effectiveness of the smart passive is clearly demonstrated.

Average of each evaluation criteria for all earthquakes



Voltage induced at one EMI system under El Centro earthquake

- The enough voltage can be generated by EMI system designed

according to structural response.

- The enough voltage can be generated by EMI system designed

according to structural response.

0 5 10 15 20 25 30 35 400

2

4

6

8

10

Time (sec)

Vol

tage

(V

)



- The smart passive system has significant advantage that it requires

no power supply during controlling structures with similar function

to other control systems

- Thus, the smart passive system was able to reduce efficiently by itself

without any power supply and control algorithm according to

structural responses.


- Smart passive control system is based on

electromagnetic induction (EMI) using MR damper.

- The EMI system takes a role of power supply and has adaptability.

- Smart passive control system is based on

electromagnetic induction (EMI) using MR damper.

- The EMI system takes a role of power supply and has adaptability.

ConclusionsConclusions

Conclusions


Conclusions

Performance verification of benchmark problem

- Smart passive system is significantly better

than passive -off and -on cases.

- Smart passive system is comparable with passive optimal and semiactive Lyapunov control case.

: It is highly energy efficient.

- Smart passive system is significantly better

than passive -off and -on cases.

- Smart passive system is comparable with passive optimal and semiactive Lyapunov control case.

: It is highly energy efficient.

Smart passive system is the superior control device. Smart passive system is the superior control device.


Thank YouThank You

for Your Attentionfor Your Attention

structural dynamics & vibration control lab 1 smart passive system based on mr damper for...

Documents