# The combined effect of temperature and humidity on the fatigue parameters and reliability of optical fiber

**ABSTRACT** The lifetime of an optical fiber depends on its environment. Previous work extensively measured and characterized the separate effects of humidity and temperature on the fatigue parameters using three different kinetics models, but the combined effect has not been determined in detail. In this work, the details of how the fatigue parameters vary with temperature in a humid environment were investigated. It was found that the kinetics model parameters were different from values obtained elsewhere in liquid water. This may be the result of differences in the apparent activation energy for fatigue in liquid and vapor environments.

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**ABSTRACT:**A new type of cable is introduced for protecting optical fiber from mechanical bending or abrupt temperature changes. It shows superior ability to protect fiber from severe bending and lowers the thermal sensitivity compared with conventional optical fiber cable. It can be used as a protection sleeve or cable in special regions. The proposed device consists of a helical composite spring, a thermal insulator (i.e., polyurethane foam) and a heat-shrinkable tube which coats the outside of the spring. These components can be acquired for a moderate price and manufactured by simple processes.Japanese Journal of Applied Physics 01/2006; 45:5804-5806. · 1.06 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**Interferometric fiber-optic gyroscopes exhibit time-dependent rate error patterns during operation due to environmental stress on the fiber coil. Short-term errors, equilibrating on the order of minutes to several hours, are attributed to nonreciprocity due to thermal gradients. Long-term rate errors, equilibrating on the order of days to weeks, have not been thoroughly addressed. In this study, we show that diffusion of moisture into or out of a sense coil can cause long-term rate errors. To calculate this effect, we measured the effect of moisture on the mechanical properties of the optical fiber coating. Using these data, we modeled diffusion in a sense coil with finite-element analysis. The rate error is calculated with an integral that is similar to that used by Shupe and others. A variation in water concentration in the coil due to diffusion causes changes in the properties of the fiber coating. This in turn produces nonreciprocal stresses on the waveguide and leads to a rate error.Journal of Lightwave Technology 07/2012; 30(14):2356-2362. · 2.86 Impact Factor

Page 1

The Combined Effect of Temperature and Humidity on the Fatigue

Parameters and Reliability of Optical Fiber

Janet L. Mrotek*† and M. John Matthewson‡

Photonic Component Reliability Group, Department of Ceramic & Materials Engineering,

Rutgers University, 607 Taylor Road, Piscataway, NJ, USA 08854-8065

ABSTRACT

The lifetime of an optical fiber depends on its environment. Previous work extensively measured and characterized the

separate effects of humidity and temperature on the fatigue parameters using three different kinetics models, but the

combined effect has not been determined in detail. In this work, the details of how the fatigue parameters vary with

temperature in a humid environment were investigated. It was found that the kinetics model parameters were different

from values obtained elsewhere in liquid water. This may be the result of differences in the apparent activation energy

for fatigue in liquid and vapor environments.

Keywords: optical fiber reliability, lifetime models, humidity, temperature

1. INTRODUCTION

Most models currently used for making lifetime predictions of optical fiber do not explicitly incorporate the details of

the service environment.1 Therefore there is an implicit assumption in such predictions that the environments relevant to

the lifetime prediction (i.e. service and proof test environments as well as the environment used to measure the fatigue

parameters) are all the same. In general these environments are not the same but some compensation for this can be

made by using “worst case” fatigue parameters (e.g., as in Ref. 2). However, clearly, if there are significant deviations

between the test and service environments reliability predictions will be erroneous. Specifically, environments more

aggressive (hotter and more humid) than typical laboratory test environments of ~25°C and 50% humidity will lead to

earlier failure while benign environments (e.g. space applications with extremely low water content) will result in much

longer lifetimes than the models predict. It is therefore clearly desirable to have lifetime models that explicitly

incorporate the character of the service environment. For this we need detailed information on how the fatigue

parameters vary with environmental factors such as temperature, humidity and pH; preferably over a broad range of

parameter values.

In earlier work3 the effect of humidity on the fatigue parameters of pristine fiber at 25°C was extensively studied and the

results were interpreted in terms of three kinetics models (the power law and two exponential forms). It was found that

the chemical kinetics model proposed by Wiederhorn and Bolz,4 which assumes that the stress at the crack tip modifies

the activation energy of the chemical reaction via an activation volume, provides the most consistent description of the

effect of humidity. Similar work that examined the effect of temperature in liquid aqueous environments5 did not favor

any one of the three kinetics models but did show that the interpretation of the results in terms of an activation barrier for

fatigue does depend on which form is used. However, a general result was found; the stress dependence of the activation

entropy is the dominant factor and that the activation enthalpy does not alone explain the observed temperature

dependence. The activation entropy increases with applied stress. A generalized chemical kinetics model for fatigue

suggested that the apparent activation parameters are not unique but will depend on the environment to some extent.6

This was later validated by comparing fatigue in pure water and in pH 7 buffered water.7 This therefore means that the

activation parameters will not be the same in liquid water and water vapor.

Up until this point, the effects of humidity and temperature have been studied independently of each other or have only

been studied in terms of their effect on strength rather than on the fatigue parameters. Duncan, France and Craig8

presented strength data which imply that the strength degradation can be solely described by the dew-point temperature,

* Formerly Armstrong; † jmrotek@patmedia.net; ‡ mjohnm@rci.rutgers.edu; 1 732 445-4534; fax 1 732 445-3258;

http://www.rci.rutgers.edu/~mjohnm/mypage/index.html

Reliability of Optical Fiber Components, Devices, Systems, and Networks II,

edited by Hans G. Limberger, M. John Matthewson, Proc. of SPIE Vol. 5465

(SPIE, Bellingham, WA, 2004) · 0277-786X/04/$15 · doi: 10.1117/12.582546

268

Page 2

thus combining the effects of temperature and humidity into one variable. However, this suggests that strength is

dependent only on the thermodynamics of the equilibrium between the vapor and condensed phases of water and does

not depend on the kinetics of the reaction between water and silica, which is clearly wrong. Armstrong et al.9 examined

this question in detail and found that the dew point temperature was not the controlling parameter - therefore the kinetics

of the reaction between water and silica does indeed play a role.

In the work presented here, we examine the dependence of both the strength and the fatigue parameters on temperature

in water vapor which complements the earlier work of Shiue and Matthewson for liquid water.5,7 Since interpretation of

such results can depend on the mathematical model used to analyze the data, three different models will be used. The

models describe how the crack growth rate, dc/dt, depends on the applied stress intensity factor, KIC

n

K

A

dt

which is designated the “power law”.10

IC

which assumes the activation energy for fatigue is reduced by an amount proportional to applied stress intensity.4

which assumes the activation energy is reduced by an amount proportional to the strain energy release rate, i.e. is

proportional to the square of the stress intensity. This form may be found by simplifying10 a more general form

proposed by Lawn.11

While of different mathematical forms, the three models each involve two parameters which have the same meaning in

each model. The Ai (i = 1…3) are pre-exponential terms which represent the overall crack growth rate and the ni which

represent how sensitive the rate is to the applied stress. If fatigue is treated as a chemical reaction whose activation

energy is modified by the applied stress, then all three models can be incorporated into absolute rate theory to give a

general form for Ai:5,6

where c0 is the increase in crack length per breaking bond at the crack tip, kB is Boltzmann’s constant, T is absolute

temperature, h is Planck’s constant,

)(Cf

is some function of the concentration, C, of the reacting species, R is the gas

constant,

0

H

∆

and

0

S

∆

are the activation enthalpy and entropy for crack growth in the limit of zero applied stress. The

same theory shows that the ni parameters can be expressed as a linear function of reciprocal temperature:

b

RT

where bH and bS represent how the activation barrier for the fatigue process is reduced by the effect of stress on the

enthalpy and entropy components of the barrier. In general, the function

depend on temperature (for example the partial pressure of water for a vapor environment or the concentration of

hydroxyl ions in liquid water) so that if an mth order reaction is assumed:

Model 1:

1

IC

I

1

K

dc

=

, (1)

Model 2:

dc

dt

An

K

K

=

22

exp

I

, (2)

Model 3:

=

2

IC

I

33exp

A

K

K

n

dt

dc

, (3)

∆

+

∆

−=

R

S

RT

H

C

(

f

h

Tk

cA

B

i

*

0

*

0

0

exp)

, (4)

*

*

R

b

n

SH

i

+=

, (5)

)(Cf

will depend on temperature since C can

m

CC(f

α=

)

(6)

then the apparent activation energy for fatigue is given by

•

∆+∆=

HmHEa0

,

where

∆H is the activation enthalpy for the concentration of the reacting species. This shows that the activation

enthalpy (and for similar reasons the activation entropy) depend on the nature of the environment.

*

(7)

•

Proc. of SPIE Vol. 5465 269

Page 3

While bH and bS have been determined for liquid environments,5 they have not been determined for a humid

environment. The purpose of this work is to address this issue since it should not be assumed the values of these

parameters would be the same in all types of environment.

2. EXPERIMENTAL

The specimen used in this study was a dual acrylate coated fiber. The fiber strength was measured at five different

faceplate velocities (1, 10, 100, 1000, 5000 µm/s) using a two-point bending apparatus.12 The strength was measured by

allowing the coated fiber to equilibrate in the appropriate environment, which was 50±1% humidity at temperatures

ranging from 5 to 55 ± ??1°C. Twenty samples were measured at each speed. At the lower speeds, up to ten specimens

could be broken simultaneously by supporting the fibers between multi-grooved faceplates. It has been shown

previously that if this fiber is properly equilibrated with the test environment the coating will not perturb the reaction

kinetics.3 Therefore, for convenience only coated fibers are studied here. The equilibration periods utilized depended

on the temperature of the test environment and ranged from overnight for the lower temperatures to one hour for the

higher temperatures. Numerical integration was used to calculate the fatigue parameters ni and Ai for each model from

the data at each temperature. The following parameter values were assumed for this analysis: critical stress intensity

factor KIC = 0.75 MPa.m1/2, crack shape parameter, Y = 1.16, and initial/inert strength σi = 12 GPa – while the numerical

results depend on these values, the trends are insensitive to them and changing these parameters would not change any of

the conclusions.

3. RESULTS AND DISCUSSION

Figs. 1 and 2 show the calculated values of ni and Ai respectively as a function of reciprocal temperature. Table 1

presents the values of bH and bS calculated from the slope and intercepts of the best fit regression lines fitted to the data

of Fig. 1 using Eq. 5. For comparison purposes, the results from Ref. 5 for pure water and pH 7 buffer are also shown.

It may be shown that slope and intercept of linear fits to the results shown in Fig. 2 may be used to estimate values for

*

0

H

∆

and

app, 0

S

∆

H*

0

slope

−=

, and

*

:5

∆

R

(8)

R

S

C

(

f

h

Tk

c

B

*

0

0

) lnln intercept

∆

++

=

. (9)

However,

known) so the apparent activation entropy in the limit of zero stress can be defined:

)(Cf

is not known (or more particularly, the parameter α in Eq. 6 is not known even if the order, m, is

)( ln

*

0

*

app , 0

CfRSS

+∆=∆

, (10)

which can be explicitly calculated from the intercept of the regression lines in Fig. 2.

Table 2.

To understand the implications of the current results it is useful to examine the earlier results in pure water and pH 7

buffer. The activation parameters shown in Tables 1 and 2 for these two environments are essentially the same within

experimental error. This is because these results were obtained for coated fiber which is an effective diffusion barrier to

the large ions in the buffer solution so the glass surface effectively sees the same environment in both cases.* Assuming

a temperature of around 300 K for the pure water and pH 7 results, the effect of stress is primarily felt through its

influence on the activation entropy since bH/T is small compared to bS (model 1) or negative which alone would impede

fatigue (models 2 and 3). Turning now to the results for the vapor environment, it is first noted that the confidence

intervals are quite large because of the narrower range of temperatures explored in the current work. However, it is clear

that the results are significantly different from the liquid environments. bH is of more importance whichever model is

used the interpret the data, because the values are larger than for the liquid environment. This difference in the

*

0

H

∆

and

*

app , 0

S

∆

are shown in

* Interestingly, when the coating is absent, stripped fibers do show different behavior in the two environments since the pH of water

varies with temperature while that of the buffer does not.7

270 Proc. of SPIE Vol. 5465

Page 4

sensitivity to stress suggests that the nature of the reactions leading to fatigue are quite different and that the common

observation that the strength in liquid is not the same as the strength in humidity in the limit of 100% saturation is not

simply explained by a difference in overall fatigue rate, but is actually a different process.

Turning now to the values of the activation enthalpy and (apparent) activation entropy in the limit of zero stress, the

entropy plays a bigger role than in the liquid environment, at least for the exponential models. While the above

arguments suggest that there is no reason why these parameters should be the same since the reaction paths are different,

one expects further differences between

app, 0

S

∆

in liquid and vapor environments because the function

will be different in both cases.

Table 1: Parameters describing the sensitivity of the activation barrier to the applied stress, as defined by Eq. 5.

Results for liquid aqueous environments from Ref. 5 are also shown for comparison. The confidence intervals

represent a 95% range.

*

)(Cf

in Eq. 10

Environment Model 1 Model 2 Model 3

50% RH bH (kJ/mol)

84 ± 25 53 ± 29

−101 ± 87

bS (J/mol K)

−80 ± 80 250 ± 100 800 ± 280

Distilled water5

bH (kJ/mol)

7 ± 100

−130 ± 30

−350 ± 60

bS (J/mol K)

180 ± 30 870 ± 110 1700 ± 200

pH 7 buffer5

bH (kJ/mol)

55 ± 91

−110 ± 40

−370 ± 60

bS (J/mol K)

160 ± 30 770 ± 120 1700 ± 200

n1

20

22

24

26

28

30

n2

48

50

52

54

1/T × 103 K-1

3.03.2 3.43.6

n3

50

55

60

65

ln(A1 /m.s−1)

-8

-6

-4

-2

ln(A2 /m.s−1)

-50

-32

-48

-46

-44

1/T × 103 K-1

3.03.2 3.43.6

ln(A3 /m.s−1)

-40

-38

-36

-34

Fig. 1: The fatigue parameter ni as a function of 1/T measured at

50% relative humidity.

Fig. 2: ln Ai as a function of 1/T measured at 50% relative

humidity.

Proc. of SPIE Vol. 5465 271

Page 5

Table 2: Activation barrier parameters for fatigue in the limit of zero applied stress. Results for liquid aqueous

environments from Ref. 5 are also shown for comparison. The confidence intervals represent a 95% range.

Environment

50% RH

Model 1

−9 ± 16

Model 2

85 ± 10

Model 3

39 ± 10

*

0

H

∆

(kJ/mol)

*

, 0 app

S

∆

∆

*

, 0 app

S

∆

∆

*

, 0 app

S

∆

(J/mol.K)

−80 ± 55

−91 ± 30

−150 ± 30

Distilled water5

*

0

H

(kJ/mol)

48 ± 8

−2 ± 14

−4 ± 9

(J/mol.K)

50 ± 30

−460 ± 40

−380 ± 30

pH 7 buffer5

*

0

H

(kJ/mol)

44 ± 8 5 ± 16

−12 ± 9

(J/mol.K)

30 ± 20

−430 ± 50

−400 ± 30

4. CONCLUSIONS

Dynamic fatigue measurements on fused silica optical fiber as a function of temperature in a humid environment have

been used to characterize the nature of the activation barrier for the fatigue process and how the barrier height is reduced

by stress. The results have been found using three different forms for the fatigue kinetics model (the power law and two

exponential forms). The values of the parameters are significantly different for each model indicating that care should

be taken interpreting fatigue data since the interpretation might depend on the model used. It is therefore recommended

that when modeling fatigue and predicting lifetimes for critical applications a range of kinetics models should be

considered in order to distinguish general results from results that are merely artifacts of the assumed kinetics model.

The activation parameters in the humid environments are different from the values found in earlier work5 for liquid

aqueous environments. This suggests that the reaction paths in the two environments are different. It is well known that

the strength in liquid and high humidity are different – the current results show that this is not simply explained by

differences in water concentration/activity but that the fatigue reaction paths are different. It was found in liquid

environments that stress decreases the activation barrier primarily via entropic effects (independent of which kinetics

model is assumed) and that the effect of stress on the enthalpy component of the activation barrier is either negligible or

impedes fatigue. In contrast, we show that while entropy is still important in humid environments, enthalpy also plays a

role although the importance of that role depends on which kinetics model is assumed.

The results presented here were obtained for a polymer coated fiber. In other work this fiber was shown to have similar

fatigue behavior when stripped of the coating using hot sulfuric acid. In particular the reaction order with respect to

humidity was found to be two.3 However, other coatings may have a significant effect on the fatigue kinetics so caution

should be used before applying our results to other coating systems.

The results presented here use short lengths of fiber which have pristine strength and do not contain large defects. For

most, though not all, applications reliability is concerned with the behavior of a few large weak extrinsic defects. Since

extrinsic defects are different in character from the “defects” in the flaw-free material, the kinetics of fatigue for weak

defects should not be inferred from the results for high strength fiber but should be measured directly (see, for example,

the paper in this proceedings by Semjonov et al. which examines the fatigue behavior of large artificial flaws).

However, the approach used here does provide a methodology for interpreting the meaning of fatigue parameters for

weak defects.

REFERENCES

1. F. P. Kapron and C. R. Kurkjian, “Reliability and standards in photonics,” Proc. XVIII Int. Cong. Glass C6-28-37

(1998).

2. “FOTP-31 - Proof testing optical fibers by tension,” TIA/EIA-455-31-C, Telecommunications Industry

Association, Washington, DC, (Feb. 1, 1999).

272 Proc. of SPIE Vol. 5465

Page 6

3. J. L. Armstrong, M. J. Matthewson and C. R. Kurkjian, “Humidity dependence the fatigue of high-strength fused

silica optical fibers,” J. Am. Ceram. Soc. 83 [12] 3100-3108 (2000).

S. M. Wiederhorn and L. H. Bolz, “Stress corrosion and static fatigue of glass,” J. Am. Ceram. Soc. 53 [10] 543-

549 (1970).

Y. S. Shiue and M. J. Matthewson, “Stress dependent activation entropy for dynamic fatigue of pristine silica

optical fibers,” J. Appl. Phys. 89 [9] 4787-4793 (2001).

M. J. Matthewson, “Chemical kinetics models for the fatigue behavior of fused silica optical fiber,” Mat. Res. Soc.

Symp. Proc. 531 143-153 (1998).

Y. S. Shiue and M. J. Matthewson, “Apparent activation energy of fused silica optical fibers in static fatigue in

aqueous environments,” J. Eur. Ceram. Soc. 22 2325-2332 (2002).

W. J. Duncan, P. W. France and S. P. Craig, “The effect of environment on the strength of optical fiber” in

“Strength of inorganic glass,” ed. C. R. Kurkjian, pp. 309-328, Plenum Press, New York, (1985).

J. L. Armstrong, M. J. Matthewson and C. R. Kurkjian, “The mechanical behavior of optical fiber as a function of

dew point temperature,” Mat. Res. Soc. Symp. Proc. 531 59-63 (1998).

10. K. Jakus, J. E. Ritter, Jr. and J. M. Sullivan, “Dependency of fatigue predictions on the form of the crack velocity

equation,” J. Am. Ceram. Soc. 64 [6] 372-374 (1981).

11. B. R. Lawn, “An atomistic model of kinetic crack growth in brittle solids,” J. Mat. Sci. 10 469-480 (1975).

12. M. J. Matthewson, C. R. Kurkjian and S. T. Gulati, “Strength measurement of optical fibers by bending,” J. Am.

Ceram. Soc. 69 [11] 815-821 (1986).

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Proc. of SPIE Vol. 5465 273

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