Microstructural Influences on Fatigue Crack Growth in Rene 88DTEric K. Sackmann and Kip Findley

School of Mechanical and Materials Engineering, Washington State University, REU 2005

IntroductionNickel-based superalloys are high alloy materials that maintain excellent strength and corrosion resistance at elevated temperatures. Consequently, these alloys are commonly used for jet engine parts (Fig 1) in the aerospace industry. The strengthening mechanism for these alloys is a face centered cubic intermetallic phase called ��(Ni3(Ti,Al)). Fatigue crack growth (FCG) is the limiting factor controlling the service life of aircraft engine parts using nickel-base superalloys. Understanding fatigue crack behavior at elevated temperatures is critical in estimating the service life of these parts. A better understanding of microstructural influences on fatigue crack propagation path is needed in order to accomplish this task. This project was designed to investigate the microstructural influences in crack growth in Rene 88DT. Specifically, the volume fraction (Vv) of Secondary �� precipitates on the fracture surface vs. Vv on the planar section, the linear roughness parameter of the fracture cross-section, and composition near the fracture surface were examined. The analysis was performed on fatigue crack growth CT specimens that were tested at 650 °C. Two microstructural conditions were examined that will henceforth be labeled N and O.

GoalsDetermine the effects of microstructure on the fatigue crack propagation path.

• Investigate how secondary �� precipitates affect the crack propagation path.

• Examine the effects of grain orientation, carbide distribution, and twins.

Determine techniques that will allow qualitative and quantitative analysis of the crack path.

• Develop stereological techniques such as volume fraction calculations, roughness parameters, etc.

• Compare qualitative and quantitative data.

Experimental ProceduresMetallography

All the samples in this project went under a 400 grit and 600 grit grind, a 6 �m and 1 �m polish, and etch. The etchant used consisted of 40mL HCl, 40mL ethanol, and 2g CuCl21. The etch time varied from 5-30 seconds depending on the sample.

Volume FractionThe volume fraction of �� precipitates was examined for both the N and O samples on the fracture surface and planar section. A 25 point grid

Fig. 5. Example of 25 point grid overlaid onto an image of a planar view for an O sample.

was laid over an SEM image of the sample, and the number of points that intersected a �� precipitate divided by the total number of points was determined to be Vv (Fig 5). An SEM was used so the small ��precipitates could be viewed. In this experiment, Vv for the planar section and fracture surface were calculated for both N and O samples. This analysis was done to determine whether the crack path is avoiding ��precipitates.

Linear Roughness Parameter (RL)RL was calculated for one sample of both N and O. RLis a measure of roughness alonga fracture surface and is calculated by dividing the total length of the fracture by the horizontal distance in the fracture interval examined (Fig. 6). This was done to observe how the roughness along the fracture surface changes as the crack length increases.

Fig. 6. SEM image of N sample showing tracing line and horizontal line for RLmeasurement.

Results

Fig. 2. SEM image near the fracture surface of an N sample showing twins and asperity near grain boundary.

Fig. 1. A typical turbine disc for a jet engine2.

Fig. 4. SEM image of fracture surface for N sample showing etched secondary/tertiary ��.

Auger Electron Spectroscopy (AES)AES, like Scanning Electron Microscopy (SEM), is a tool used forsurface analysis. These analysis techniques both use a high voltage electron beam that has been focused by a series of magnets to a fine point on the sample. Like SEM, AES utilizes the secondary electronsthat are emitted from the surface of the sample to create an image; however, in AES, the energy of Auger electrons that are emitted (Fig. 7) are also detected and used to identify elements presentdirectly on the surface (~3nm). Using AES, a map of Ti and Al content near the fracture surface was made for O sample. Fig. 7. Schematic3 showing

fundamental concepts of AES.

Fig. 8. (a) Image of AES Ti concentration map inset onto an SEM Image FCG. (b) Map of Ti concentration over a FCG sample.

The AES showed a uniform distribution of Al over the tested area, however, some sites were noteworthy on the Ti scan. As shown in Fig. 8, small areas showed high traces of Ti concentration. These are likely carbides because of the size and appearance. While no concrete conclusions could be derived from this data, the results obtained makes AES a very promising tool for future work in identifying carbides, �� precipitates, and overall composition of key alloying elements that potentially influence the fatigue crack growth in Rene 88DT.

The experiments run during the course of examining Rene 88DT showed several conclusive results. An adequate etching technique was established for both N and O samples. The volume fraction was successfully obtained, and linear roughness measurements were calculated and analyzed. The fatigue fracture mechanism was also determined.

Volume FractionVV was calculated for both N and O samples and compared (Table I). The values obtained for the microstructure were considerably higher than those obtained for the fracture surface. When

comparing the standard deviation for measurements taken on the fracture surface and microstructure, there are no obvious trends. Overall, the values of average VV are similar for the N and O samples, with the values for O being lower. A %diff of 4.05% wasObtained when comparing VVfor the microstructures of N and O, and 1.9% when comparing VV for the fracture surfaces.

RL

RL for the area along the fracture surface for both N and O samples were obtained and graphed (Fig. 11 and 12) as RL vs. distance (�m). Both N and O samples became more tortuous as the crack length increased. The graph for the O values consistently increased while the N values ultimately increase, but dipped near the middle of the graph. Regression was not an effective tool in either graph.

EtchingGrain boundaries, Twin boundaries, Primary/Secondary �� precipitates, and carbides were successfully etched out using the aforementioned waterless Kalling’s etchant. Using this etchant, the samples would generally etch in ~15 seconds.

Linear Roughness Parameter of N sample

1

1.05

1.1

1.15

1.2

0 2000 4000 6000 8000 10000 12000 14000

Distance (microns)

R(L

)

Linear Roughness Parameter forO Sample

0

0.5

1

1.5

2

0 2000 4000 6000 8000 10000

Dis tance (microns)

R(L

)

Fig. 11. Graph showing gradual increase RL as crack length increases.

Fig. 12. Graph showing high variation in RLvalues with an ultimate overall increase.

Fatigue Fracture Mechanism

The fatigue fracture surfaces showed evidence of mixed mode failure. Evidence of both transgranular and intergranular fracture is present, however, the fracture mechanism appears to be largely transgranular (Fig. 3).

Discussion

ConclusionThe analysis done on Rene 88DT led to several useful conclusions:

• The fatigue fracture mechanism for this material at 650°C is mixed, showing some intergranular and transgranular cracking, but the mechanism is largely transgranular.

• The linear roughness parameter increases as the crack length increases.

• The volume fraction of �� precipitates is significantly less on the fracture surface than in the bulk microstructure, indicating that the crack is preferentially avoiding �� precipitates.

• Twins, grain boundaries, carbides/borides, and �� precipitates can be successfully etched in Rene88DT using the waterless Kalling’s etchant.

Future WorkAlthough several conclusions were reached during this project, there are many possibilities for future work on this topic. After qualitatively examining the cross-section of the fracture surface, grain orientation appears to play more of a role than initially thought, and interesting conclusions may come from investigating this aspect. AES appeared to be a useful tool for surface composition analysis, and could be useful in identifying precipitates that are too small for Energy Dispersive Spectroscopy (EDS) to probe. Another method that could show cracking tendencies is looking for asperities (qualitatively), and focusing on those areas for microstrucuraltendencies. Establishing correlations between asperities and microstructural features would be revealing of fatigue crack growth. In this project, RL was the only roughness parameter investigated, but in future work other roughness parameters could be useful stereological tools.

References1 Techniques for microstructural characterization of powder-processed nickel-based superalloys, Agnieszka M. Wusatowaska-Sarnek, Uninversit of Conneticut.2 www.turbine-controls.com/rot.htm3 www.aquila.html

AcknowledgementsKip Findley, Katherine Chen, Linda Vanasupa, Scott Lea and EMSL. This work was supported through the National Science Foundation: Division of Materials Research REU site program under grant number 0453554.

Sample Preparation and MicrostructureThere was considerable difficulty in the sample preparation required for the data to be gathered. The practical issues with grinding and polishing preparatory work were amplified near the fracture surface. Both polishing and etching was difficult in this area, which may play a direct role difficulties experienced in microstructural analysis. Since Electron Backscatter Detection (EBSD) and AES both require a polished sample, the difficulties encountered in sample preparation may become an issue in future work. The Kalling’s solution worked well in etching out twins (Fig. 2), �� precipitates, and grain boundaries. When inspecting Fig. 2, there appears to be an asperity that is created directly after a grain boundary. This may be an indication that grain orientation could be significant in the fatigue crack propagation.

Volume FractionAs anticipated, VV of �� precipitates on the fracture surface was considerably less than VV in the bulk of the specimens. Since �� precipitates are thought to be the strengthening mechanism in nickel-base superalloys, it is likely that the crack would grow preferentially around these precipitates. However, there were some considerations that must be factored into the volume fraction calculations. First, the Kalling’s solution is required to etch a non-polished surface, which generally may not etch well, although in this case it appeared to. Another consideration is the nonuniform nature of the �� precipitate etched areas that requires the analyzer to choose which areas to test. Clearly distinguishing ��precipitates is also a problem that occurred on the fracture surface. There is difficulty in distinguishing small portions ofsecondary �� and tertiary �� precipitates (Fig. 4). Additionally, topographical changes that appeared to be a �� precipitates were difficult to discern as well.

Linear Roughness ParameterThe Linear Roughness Parameter was calculated to give an idea of how the roughness changes as the crack length grows. It was initially hypothesized that the values would decrease over the length of the crack because the crack’s roughness would become less dependent on microstructural influences, and more on the increasing stress concentration around the crack tip as the crack grows. The data showed convincingly that the roughness was increasing as the crack length increased, and there are a few explanations for this. One likely reason would be that the crack may have more of an intergranular fracture mechanism (rather than transgranular) as the crack grows. Since the average grain size of the grains in the N and O samples were ~20 �m and the precipitates the crack might go around/through are less than a micron on average, the asperity induced by a grain boundary would be much larger. Fatigue striations may also be playing a small role in this behavior. The amount of fatigue striations or striation spacing increases may be an indication of an overall increase in stress, which would result in more crack path tortuositythan the area near the pre-crack.

The graphs that were obtained from the data also showed interesting results pertaining to future RL calculations. The N sample more convincingly showed a trend of increasing roughness. Sample N SEM images were taken at 2067x magnification, while the O sample images were taken at 402x. This indicates that the resolution of the images collected plays a large role in the accuracy of the RL and must be taken into consideration.

Fig. 3. SEM image of N sample showing faceted fracture surface.

(a) (b)

Fig. 9. SEM image showing lines scanned for Ti and Al.

Figure 9 displays data collected for Al and Ti. The figure shows a Ti spike (blue) that directly correlates with what appears to be a precipitate in Figure 10. Again, AES shows potential to be a useful tool in surface composition analysis.

Fig. 10. Scan of line 2 showing Ti peak on far right of graph.

Sample N O

VV FS 0.263 0.258

VV M 0.395 0.379

Std. Dev. (F) 0.103 0.0881

Std. Dev. (M) 0.0447 0.106

Table I: RL Data comparing N and O