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MODELING OF INDUCTION HARDENING PROCESSES PART 2: QUENCHING AND HARDENING. Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong. Acknowledgement: This project is partially supported by Delphi and CHTE at WPI. Dr. Q. Lu was involved in the early work of the project. http://me.wpi.edu/~camlab.

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modeling of induction hardening processes part 2 quenching and hardening
MODELING OF INDUCTION HARDENING PROCESSES PART 2: QUENCHING AND HARDENING

Dr. Jiankun Yuan

Prof. Yiming (Kevin) Rong

Acknowledgement: This project is partially supported by Delphi and CHTE at WPI. Dr. Q. Lu was involved in the early work of the project.

http://me.wpi.edu/~camlab

objectives
Objectives
  • To develop a numerical modeling system for analyzing quench cooling and hardening processes based on temperature field data after induction heating.
  • To provide temperature distribution in workpiece at any time in a quenching process
  • To provide continuous cooling curves (CCC) of any location in workpiece, for phase transformation analysis.
  • To build an algorithm to analyze phase transformation in quench cooling processes, based on time-temperature-transformation (TTT) and CCC curves.
  • To provide time traces of volumetric content of martensite, pearlite and bainite formed in cooling.
  • To formulate a relationship between martensite content and hardness values, and to provide hardness patterns formed after quenching process.
  • To investigate key parameters (input AC power, frequency and gap between coil and workpiece) effects on final hardening patterns.
slide3
Principle: Phase TransformationPhase transformation kinetics from austenite to pearlite, bainite and martensite

Koistinen-Marburger modelfor martensite content determination

TTT diagram

r= 0.01-0.015

(fs,ts)

Avrami modelfor fp, fbdetermination in isothermal transformation

(fe,te)

Generally

fs=0.5%, fe=99.5%

TTP curve

ti

Ms

For continuous cooling , fp, fbcan be determined using following expressions

  • Ms: Martensite start temperature
  • Martensite can only be formed from austenite after WP temperature lower than Ms
principle relationship between martensite content and hardness
Principle:Relationship between martensite content and hardness

fm

HRC

0.5

47.2

0.8

50.3

0.9

53.7

0.95

56.3

0.99

58.8

Principle: Hardeness Analysis

Aim of hardening analysis

0.47%

General expression:

Page 144, <<Steel and its Heat treatment>>, Karl-Erik Thelning

Coefficients a,b,c varying with carbon content

For AISI 1070, 0.7% carbon, a=80.91,b=97,c=81.61

case study temperature field variation in water quenching process
Case Study:Temperature Field Variation in Water Quenching Process

t=0.5s

Total quenching time tq = 40s

t=2s

f=9600Hz s=1.27mm J=1.256e6 A/m2

t=40s

t=8s

case study cooling curves and hardening pattern
Case Study: Cooling Curves and Hardening Pattern

Inside points along contour line T=8150C

Surface points

Material: Carbon Steel, AISI 1070

Hardness pattern form numerical simulation

Automotive parts from Delphi Inc., Sandusky,Ohio

case study gap effect hardening pattern variation with tolerance
Case Study: Gap Effect - Hardening Pattern Variation with Tolerance

Tolerance= - 0.0025”

Tolerance= 0”

S=1.27mm

f=9600Hz

J=1.265e6

S=1.2065mm

f=9600Hz

J=1.265e6

Tolerance= + 0.0025”

Fig. Hardening depth variation with gap between coil and workpiece under three different frequencies.

S=1.3335mm

f=9600Hz

J=1.265e6

  • Hardening depth decreases with air gap distance
power effect hardening pattern variation with coil ac current density
Power Effect - Hardening Pattern Variation with Coil AC Current Density

Fig. Hardening depth variation with input current density with f=9600Hz, s=1.27mm

  • Case depth increase with input AC power
hardening pattern variation with input ac frequency
Hardening Pattern Variation with Input AC Frequency

(a) f=5000Hz

(b) f=9600Hz

Fig. Hardening depth variation with input current frequency with J=1.256e7 (A/m2), s=1.27mm

  • Case depth decrease with input AC frequency.

(c) f=15000Hz

summary
Summary
  • A quenching and hardening modeling system was developed with the following capabilities.
  • (1) Provide workpiece temperature distribution at any time.
  • (2) Provide cooling curve data of any location in workpiece.
  • (3) Simulate the phase transformation process and predict volume
  • fraction of Pearlite, Bainite, Martensite formed in cooling process.
  • (4) Provide desired hardness pattern through proper simulation of coil
  • design and optimum combination of control parameters.
  • (5) Investigate parameters effects on final hardness pattern, including
  • gap effect, AC frequency effect and current density effect.
  • Applied the developed system to investigate the hardening process on a complex surface of an automotive spindle.