Using Direct Current Potential Drop Technique to Estimate Fatigue Crack Growth Rates in Solid Bar Specimens under Environmental Assisted Fatigue in Simulated Pressurized Water Reactor Conditions
Abstract
:1. Introduction
- Phase 1: Crack nucleation. It comprises the number of fatigue cycles required to create a crack with a certain length (e.g., one grain) in a previously non-cracked material. Typically, fatigue crack nucleation may take place in two different conditions: material free of macroscopic defects, and material containing macroscopic defects (e.g., notches). In the first case, nucleation requires more fatigue cycles and represents a larger proportion of the total fatigue life. Micromechanisms of crack initiation have been widely analyzed and the reader is referred to the literature (e.g., [10,11]). When testing solid bars without macroscopic defects, fatigue crack initiation sites are located on the specimen surface, with a big proportion of the total fatigue life being consumed in the nucleation phase (80% can be taken as a reference [12]). Moreover, in solid specimens, the DCPD technique is able to detect this phase when multiple fatigue initiates occur simultaneously, but it is not possible to distinguish among the different initiation sites which crack will be the dominant one, propagating and causing the final failure.
- Phase 2: Crack propagation. This includes short crack growth and long crack growth. The first stage is governed by the material microstructure and corresponds to the number of load cycles required to grow a crack from the crack-nucleated grain until the crack is long enough to be modeled by bulk material properties, whereas the second one corresponds to a stage controlled by the bulk material properties and, in case of high cycle fatigue conditions, conventional linear elastic fracture mechanics (LEFM) is valid (e.g., Paris law [13]). In this second sub-phase, crack propagation is stable and continuous, the fatigue striations are generally well-defined, and the process is more easily analyzed by the DCPD technique. The crack progression marks may be observed with scanning electron microscopy (SEM) analysis. The striation pattern is a signal of microscopic plasticity and it is generated by blunting and re-sharpening of the crack-tip, during every load cycle (Laird’s mechanism [14]). The striation spacing may also be used to estimate the local fatigue crack propagation rate (da/dN).
- Phase 3: Final failure. Fatigue crack propagation becomes unstable and the remaining cross-section can no longer resist the applied load, leading to final fracture or plastic collapse. This stage is not analyzed in the present research, as tests were stopped when a certain load drop was achieved.
2. Materials and Methods
2.1. Material and Test Setup
2.2. From DCPD Measurements to Crack Geometry
- Obtain the DCPD signal during the fatigue test. This allows the DCPD vs. time curve to be obtained. Given that the loading frequency is also known, the DCPD vs. number of cycles (N) curve may also be obtained.
- Definition of geometrical model, which provides the relation between 1/Sr and the crack length through Equations (3) and (4)). The 1/Sr vs. crack length (a) curve is defined.
- Measurement of the corresponding crack length at failure (af), for which the number of cycles is also known (Nf).
- Definition of a0 (i.e., 200 μm) and, obtainment of the corresponding number of cycles for crack initiation to be completed (N0, see Figure 6).
- Once (a0, N0) and (af, Nf) are defined, the obtainment of the average CGR is straightforward. If the whole crack length vs. number of cycles curve (e.g, see Figure 7 below) were needed, it would be necessary to proceed as in step d), but considering different crack sizes on the geometrical model.
3. Results
- (a)
- There is a good correlation between the values measured by fractography and those estimated by potential drop.
- (b)
- The estimated values (points) are above the curve fitted by Shack and Kassner (originally developed in NUREG/CR-6176 [15]), which corresponds to oxygenated environments. This agrees with the fact that the CGR in environments with low oxygen content (PWR) increases when compared with the CGR in environments with higher oxygen content (boiling water reactor, BWR) [38].
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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C | Cr | Cu | Mn | Mo | N | Ni | P | S | Si |
---|---|---|---|---|---|---|---|---|---|
0.029 | 18 | 0.02 | 1.86 | 0.04 | 0.056 | 10 | 0.029 | 0.004 | 0.37 |
Test | Ra (μm) | Rt (μm) | Gauge Length (mm) | Diameter (mm) | Strain Amplitude (ɛm, %) | Rising Strain Rate (ɛ, %s−1) | Frequency (Hz) |
---|---|---|---|---|---|---|---|
CI6 | 1.632 | 14.470 | 10.0 | 3.79 | 0.60 | 0.01 | 0.0076 |
CI11 | 0.041 | 0.764 | 10.0 | 3.99 | 0.60 | 0.01 | 0.0076 |
CI12 | 0.028 | 0.351 | 10.0 | 3.99 | 0.23 | 0.01 | 0.0198 |
CI15 | 0.031 | 0.404 | 10.0 | 3.98 | 0.60 | 0.01 | 0.0076 |
CI16 | 0.041 | 0.490 | 10.0 | 4.00 | 0.60 | 0.01 | 0.0076 |
CI18 | 0.029 | 0.335 | 10.0 | 3.99 | 0.30 | 0.01 | 0.0152 |
CI19 | 2.015 | 17.895 | 10.0 | 3.75 | 0.60 | 0.01 | 0.0076 |
CI20 | 1.615 | 14.613 | 10.0 | 3.60 | 0.30 | 0.01 | 0.0152 |
CI22 | 1.948 | 17.077 | 10.0 | 3.65 | 0.23 | 0.01 | 0.0198 |
Parameter | Value |
---|---|
Temperature | 300 °C ± 3 °C |
Pressure | 150 bar |
Li content | 2 ± 0.2 ppm as LiOH |
B content | 1000 ± 100 ppm as boric acid |
Dissolved hydrogen | 25 ± 5 cc(STP)H2/kg (standard temperature and pressure (STP): 1 bar, 25 °C) |
pH @300 °C | ≈6.95 |
pH @25 °C | ≈6.41 |
Conductivity @25 °C | ≈30 µS/cm |
Anionic contamination | <10 ppb |
Oxygen | <5 ppb |
Cationic contamination | <100 ppb |
Total organic carbon (TOC) | <200 ppb |
Test | Strain Amplitude (%) | Load Drop (%) | Final Crack Length (mm) | Average CGR (DCPD) (mm/s) | Average CGR (Fractography) (mm/s) | N25 (Cycles) |
---|---|---|---|---|---|---|
CI6 | 0.60 | 100 | 3.321 | 3.79 × 10−5 | 3.51 × 10−5 | 673 |
CI11 | 0.60 | 31 | 1.907 | 1.98 × 10−5 | 1.79 × 10−5 | 1414 |
CI12 | 0.23 | 36 | 2.422 | 1.14 × 10−5 | - | 11,018 |
CI15 | 0.60 | 35 | 3.734 | 1.64 × 10−5 | - | 1311 |
CI16 | 0.60 | 50 | 2.760 | 1.81 × 10−5 | - | 1447 |
CI18 | 0.30 | 32 | 2.175 | 1.33 × 10−5 | 1.29 × 10−5 | 5241 |
CI19 | 0.60 | 39 | 2.366 | 3.72 × 10−5 | 1.74 × 10−5 | 1004 |
CI20 | 0.30 | 35 | 2.033 | 2.06 × 10−5 | 2.12 × 10−5 | 3326 |
CI22 | 0.23 | 51 | 2.727 | 2.36 × 10−5 | 2.25 × 10−5 | 5800 |
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Arrieta, S.; Perosanz, F.J.; Barcala, J.M.; Ruiz, M.L.; Cicero, S. Using Direct Current Potential Drop Technique to Estimate Fatigue Crack Growth Rates in Solid Bar Specimens under Environmental Assisted Fatigue in Simulated Pressurized Water Reactor Conditions. Metals 2022, 12, 2091. https://doi.org/10.3390/met12122091
Arrieta S, Perosanz FJ, Barcala JM, Ruiz ML, Cicero S. Using Direct Current Potential Drop Technique to Estimate Fatigue Crack Growth Rates in Solid Bar Specimens under Environmental Assisted Fatigue in Simulated Pressurized Water Reactor Conditions. Metals. 2022; 12(12):2091. https://doi.org/10.3390/met12122091
Chicago/Turabian StyleArrieta, Sergio, Francisco Javier Perosanz, Jose Miguel Barcala, Maria Luisa Ruiz, and Sergio Cicero. 2022. "Using Direct Current Potential Drop Technique to Estimate Fatigue Crack Growth Rates in Solid Bar Specimens under Environmental Assisted Fatigue in Simulated Pressurized Water Reactor Conditions" Metals 12, no. 12: 2091. https://doi.org/10.3390/met12122091