vital outcomes so far

Vital outcomes so far• tools to identify curving and rolling noise

sourcesand

• allow prescription of reliable mitigation methods and to manage them.

• A standard process to select mitigation strategies based on costs and benefits

Motivation for Research– Rail noise issue now recognised– Noise barriers are a “blunt instrument”– Some aspects are relatively simple to address by:

• changing operational procedures: yard noise; horns; idling • standard industrial noise control: locomotives, traction equipment • Vibration isolation: vibration reducing track

– but other aspects not simple, requiring research:• Curve noise • Noise source identification• tools to communicate cost / benefit of noise control

Major Tools Now Available1. Curving noise

a. Mechanism identification: On-board and Trackside located.b. Standard definitions.c. Key mechanisms consolidated leading to effective mitigation.d. Mitigation method evaluation.

2. Rolling noisea. Noise prediction software (RRNPS) is now available, calibrated to Australian situations.b. Noise separation algorithm to direct mitigation method selection and management.c. A scientific method for evaluating potential mitigation strategies is now available.

3. Cost / benefit analysisa. A standardised approach to benefit and cost identification.b. A step by step guide to noise mitigation and management.c. Advice on the effectiveness of potential noise mitigation methods.

General Process

General Process

General Process

Curve Noise Mechanisms

Conventional theory

• Curve squeal– Lateral sliding

between the Inner wheel tread and rail head

• Flanging noise– HIGH rail flange

contact

New understanding

• Curve squeal– Flange contact on both

rails– Wheel tread on top of

both rails

• Flanging noise– HIGH and LOW rail

flange contact

8

Curve Noise Mitigations (1)

9

Curve Noise Source Identification (2)

10

connection between bolster and carbody

connection between bolster and sideframe

connection between sideframe and axlebox

Vehicle Dynamics Modelling

AOA of the Leading Axles by varying centre bowl friction and warp stiffness

new half-worn fully-worn-20

-18

-16

-14

-12

-10

-8

-6

A3

A2

AO

A o

f th

e le

ad

ing

axl

e(m

rad

)

friction wedge worn condition

centre bowl = 0.33case A1-A3 centre bowl = 0.5, case A4-A6 centre bowl = 0.1, case A7-A9

A1

A4

A5

A6

A7 A8A9

1. The major influencing factors increasing AOA are, in sequence:• the centre bowl friction• the warp stiffness• the friction coefficient of sidebearers and• the preload of sidebearers • Rail gauge corner lubrication makes the leading wheelset AOA becomes

larger

2. The worst combination of bogie parameters in regards to AOA is• high centre bowl friction level combined with• low warp stiffness due to wedge rise.

17th July 2012

Summary

RRNPS Rolling Noise Prediction

Noise and Roughness Separation-Set Up

Ballast

Sleeper

Rail

Pad

A1

A2

A3

A4 A5R1, 2

O1, 2

Stick

7.5m

A1, 2

R1 R2

A3, 4

A5

O1 O2

M1

M2

Field Trial - Noise Separation Method

102

103

20

30

40

50

60

70

80

Frequency(Hz)

So

un

d P

resu

re L

eve

l(d

B r

e 2

0 P

a)

Total radiationVehicle radiationRail radiationSleeper radiation

Field Trial – Roughness Separation Method

31.5 20 12.5 8 5 3.15 2 1.25 -30

-25

-20

-15

-10

-5

0

5

10

15

20

Wavelength(cm)

Ro

ug

hn

ess

(dB

re

1 m

)

Total roughness variation rangeTotal roughness mean valueRun 1Run 2

Economics of Noise Mitigation Strategies

Figure 1: Major "Players" and Transactions that Affect Rail Management

What it means for you• NOW we have the tools to identify curving and

rolling noise sources• CAN use the tools to allow prescription of

reliable mitigation methods and to manage them.

• HAVE a standard process to predict or diagnose noise sources and select mitigation strategies based on costs and benefits

Who to Contact?

• Richard Dwight: radwight@uow.edu.au