My research focuses on the casting defect characteristics and the dynamic loading fracture mechanisms of high-speed train gearbox materials. The gearbox is a critical component of the running gear in high-speed trains, and its service environment is extremely harsh. Fatigue cracks frequently initiate in the gearbox housing during service, posing a serious threat to passenger safety and property. In this thesis, I systematically investigate the relationship between casting defect populations and fatigue crack initiation and propagation in a cast aluminum gearbox housing removed from a high-speed train that had operated approximately 1.2 million kilometers. I combine advanced characterization techniques, synchrotron radiation X-ray tomography, in-situ fatigue testing, and finite element simulation to reveal how the size, position, morphology, and orientation of pores affect the fatigue performance of the gearbox material. A central contribution of my work is the proposal of a coupling coefficient \(f\), defined as the effective pore radius divided by the offset distance from the pore to the free surface, which quantifies the coupled effect of pore size and pore location on fatigue crack initiation. This coupling coefficient can be used to predict the failure location in high-speed railway gearbox materials.
Introduction
High-speed trains are among the most important transportation vehicles in modern railways. Their design must address numerous safety, stability, and reliability concerns, particularly for components under the vehicle body. The gearbox, as a key part of the running gear, is subjected to complex alternating loads, vibrations, and environmental corrosion. In China, more than one hundred gearbox crack incidents have been reported since the introduction of high-speed EMUs. Common failures include fatigue cracks in the housing, bearing failures, and gear tooth damage. Figure 1 shows two typical failure modes: fatigue cracking of the housing and bearing failure. Because the gearbox housing is a large aluminum casting, it inevitably contains casting defects such as gas pores and shrinkage cavities. These casting defect features strongly influence the fatigue strength and crack nucleation behavior. Traditional manufacturing methods for high-speed train gearboxes are still based on low-pressure casting, and additive manufacturing techniques such as selective laser melting are not yet widely adopted. Therefore, understanding how casting defects control the fatigue life of the gearbox material is essential for ensuring the reliability and safety of high-speed trains.
The gearbox housing in my study is a split-type gearbox, consisting of an upper and a lower housing. The upper housing contains motor mounting seats, inspection windows, lifting lugs, and ventilation holes, while the lower housing includes oil level inspection windows, oil filling holes, oil sump, and protective plates. Both housings have external reinforcing ribs. The material is Al-7Si-0.4Mg cast aluminum alloy, which is widely used for high-speed train gearboxes. The microstructure consists of an \(\alpha\)-Al matrix, eutectic Si particles, Mg\(_2\)Si precipitates, and Fe-rich intermetallic particles. During solidification, shrinkage cavities and gas pores form due to inadequate feeding and gas entrapment. These casting defects are known to be the most critical factors controlling the fatigue life of cast aluminum components. However, most existing fatigue life prediction models only consider a single factor, such as pore size, while ignoring the combined effect of pore size and pore location. My work aims to fill this gap by introducing a dimensionless coupling coefficient that captures the coupled influence of pore size and distance to the free surface. This approach allows me to predict which pore is most likely to nucleate the fatal fatigue crack.
Experimental Materials and Methods
The gearbox material was cut from the upper housing near the inspection window of a high-speed railway gearbox. The maximum design speed of the gearbox was 5900 r/min (approximately 420 km/h). The chemical composition was determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Table 1 lists the measured composition. The silicon content is 6.83 wt.%, which is typical of A356 cast aluminum alloy. The ultimate tensile strength and yield strength of the gearbox material were 287 MPa and 236 MPa, respectively.
| Si | Fe | Mg | Sr | Al |
|---|---|---|---|---|
| 6.83 | 0.13 | 0.283 | 0.02 | Balance |
To characterize the microstructure and phase constituents, I used X-ray diffraction (XRD) with a PANalytical-Empyrean diffractometer equipped with Co Kα1 radiation, scanning in the 20°–110° range. Electron backscatter diffraction (EBSD) was employed to reveal the grain structure, secondary phase particle size distribution, and local misorientation. For EBSD, a thin slice was cut from the gearbox scrap, ground with SiC paper, and electropolished to obtain a flat, stress-free surface. A region of approximately 0.5 × 0.5 mm was scanned to characterize the secondary phase particles. Scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) was used for fracture surface observation and micro-area compositional analysis.
Synchrotron radiation X-ray microtomography (SR-μCT) was carried out at the BL13W1 beamline of the Shanghai Synchrotron Radiation Facility (SSRF). In-situ fatigue tests were performed on cylindrical specimens with a gauge diameter of 1.2 mm. The loading frequency was 10 Hz, and the stress ratio was \(R = 0.1\), with a maximum stress of 174 MPa. Several interrupted fatigue tests were performed at 0, 6000, 8000, and 10,000 cycles to track the evolution of cracks from casting defects. The X-ray photon energy was 21 keV, and the spatial resolution was 1.48 μm. Three specimens were tested to verify repeatability. After the in-situ tests, the projection images were reconstructed using phase retrieval and filtered back-projection algorithms. The resulting slices were imported into Avizo and Amira software for three-dimensional visualization and quantitative analysis of pore volumes, sizes, positions, roundness, and aspect ratios.
For finite element analysis, I converted the three-dimensional reconstructed pore models into solid models using Geomagic Studio. The mesh-based STL files were imported into Geomagic Studio and converted to NURBS surfaces. The solid models were then imported into SolidWorks to remove small pores (radius < 60 μm), which were found to have negligible effect on fatigue crack growth. Finally, the simplified geometry was imported into ABAQUS for stress concentration analysis. A cylindrical matrix model with a diameter of 3.2 mm and a length of 10 mm was created. The left end of the cylinder was fully fixed, and a uniform tensile stress of 50 MPa was applied to the right end. Both ideal spherical pores and actual reconstructed pore geometries were considered to investigate the effect of pore morphology on stress concentration.
Microstructural Characterization Results
The optical micrographs of the gearbox material at different magnifications show a typical cast microstructure consisting of coarse dendritic \(\alpha\)-Al grains and eutectic regions. At higher magnification, I observed platelet-like eutectic Si particles and some intermetallic compounds. The X-ray diffraction pattern, shown in Figure 3, confirms the presence of Al, eutectic Si, Mg\(_2\)Si, and Al\(_2\)O\(_3\). The Al\(_2\)O\(_3\) phase is likely formed by surface oxidation of the aluminum matrix. The Mg\(_2\)Si phase is the main strengthening precipitate in this alloy, and its presence is consistent with the addition of Mg to enable age hardening.
EBSD analysis provided further insight into the microstructure. The inverse pole figure (IPF) map shows randomly oriented equiaxed grains with sizes ranging from 100 to 500 μm. Approximately 43.75% of the grains have an equivalent diameter between 100 and 200 μm, while only 2.78% of grains fall in the 400–500 μm range. The image quality (IQ) map reveals that secondary phase particles are mainly micrometer-sized, with sizes ranging from 1 to 4 μm and an average size of 2.72 μm. The size distribution is skewed toward smaller particles, with 59.79% of particles having a radius less than 1 μm. The Kernel Average Misorientation (KAM) map shows a low local misorientation in the \(\alpha\)-Al matrix (0–1°), indicating a low density of geometrically necessary dislocations (GNDs). However, the grain boundaries and interfaces between the matrix and secondary particles exhibit higher GND density, which I attribute to the lattice mismatch between the \(\alpha\)-Al matrix and the second-phase particles.
The SEM and EDS elemental maps confirm that the material consists of an Al matrix, Si particles, Fe-rich intermetallics, and Mg-Si precipitates. The Fe-rich phase appears in both needle-like β-AlFeSi and Chinese-script π-Al\(_8\)Si\(_6\)Mg\(_3\)Fe morphologies. The presence of these hard, brittle particles is known to influence fatigue crack initiation and propagation. The EDS maps show that Mg is uniformly distributed, mainly in the form of Mg\(_2\)Si, while Fe is present as segregated intermetallic particles.
Pore Characteristics from Synchrotron Tomography
Synchrotron radiation X-ray tomography allowed me to visualize the internal casting defect structure of the gearbox material in three dimensions. Figures 3–5 show the quantitative distributions of pore size, roundness, and aspect ratio. The pore radius distribution in Figure 4 follows a roughly log-normal distribution, with an average radius of 16 μm. About 93.1% of pores have radii between 0 and 30 μm, while the largest pore observed has a radius of 136 μm. The minimum resolved pore radius is 5 μm. The wide range of pore sizes indicates that the casting process creates a heterogeneous defect population, which complicates fatigue life prediction. The pore roundness, defined as
\[
\psi = \frac{6\sqrt{\pi} V}{S^{3/2}},
\]
where \(V\) is the pore volume and \(S\) is the pore surface area, was calculated for all pores. The distribution shows that 84.3% of pores have roundness values between 0.7 and 1.1, indicating that most pores are nearly spherical or slightly elliptical. However, larger pores tend to have lower roundness, meaning that their shape becomes highly irregular and wrinkled. The aspect ratio distribution in Figure 6 shows that 88.7% of pores have aspect ratios below 2.0, and almost all pores below 1.2 μm in radius have aspect ratios less than 2.0. The maximum aspect ratio observed is 3.8. The statistical distributions of pore size, roundness, and aspect ratio demonstrate that the casting defects in the gearbox housing are randomly distributed in both size and morphology, making the prediction of fatigue failure particularly challenging.
| Parameter | Average | Maximum | Minimum | Percentage (range) |
|---|---|---|---|---|
| Pore radius (μm) | 16 | 136 | 5 | 93.1% (0–30) |
| Roundness | — | 1.0 | 0.53 | 84.3% (0.7–1.1) |
| Aspect ratio | — | 3.8 | 1.06 | 88.7% (< 2.0) |
In addition to the smaller pores, I identified twelve large pores (radius > 60 μm) that were tracked individually during the fatigue test. These large pores are expected to dominate the fatigue crack initiation process. Table 3 lists the volume \(V\), effective radius \(r\), offset distance \(d\), and coupling factor \(f\) for each of the twelve large pores. The effective radius is calculated from the pore volume using the equivalent sphere formula:
\[
r = \left( \frac{3V}{4\pi} \right)^{1/3}.
\]
The offset distance \(d\) is defined as the shortest distance from the pore center to the free surface along the direction perpendicular to the loading axis. For pores close to the surface, \(d\) is small; for internal pores, \(d\) is large. The coupling factor is defined as
\[
f = \frac{r}{d}.
\]
To avoid singularities when \(d\) approaches zero, I used an effective offset length that accounts for the pore size. For a pore that intersects the free surface, the offset length is taken as the distance from the pore surface to the free surface, normalized by the pore radius. In my final formulation, I define the coupling factor as
\[
f = \frac{V^{1/3}}{d + \alpha r},
\]
with \(\alpha\) chosen to ensure a finite value when the pore is tangent to the surface. However, for simplicity and direct comparison with experimental data, I used the simpler expression \(f = r/d\) for the large pores listed in Table 3, where \(d\) is the distance from the pore center to the nearest free surface. For surface-tangent pores, \(d = r\), and the coupling factor becomes unity. In the in-situ samples, pore 10 had the smallest d value (3.02 μm) and the largest f value (24.09), while pore 8 had the largest d value (418.93 μm) and the smallest f value (0.21). The pore volume and offset distance are not correlated, demonstrating that casting defect size and position are statistically independent.
| Pore no. | Radius \(r\) (μm) | Offset distance \(d\) (μm) | Coupling factor \(f = r/d\) |
|---|---|---|---|
| 1 | 96 | 5.35 | 17.94 |
| 2 | 91 | 296.78 | 0.31 |
| 3 | 100 | 20.42 | 4.86 |
| 4 | 136 | 158.01 | 0.86 |
| 5 | 103 | 402.25 | 0.26 |
| 6 | 119 | 290.93 | 0.41 |
| 7 | 68 | 34.57 | 1.97 |
| 8 | 86 | 418.93 | 0.21 |
| 9 | 86 | 33.58 | 2.55 |
| 10 | 73 | 3.02 | 24.09 |
| 11 | 63 | 351.81 | 0.18 |
| 12 | 80 | 140.98 | 0.57 |
Fatigue Crack Initiation and Propagation
The in-situ fatigue tests combined with synchrotron tomography enabled me to observe crack initiation and growth from individual casting defects in real time. Figure 9 shows the three-dimensional reconstructed volume of the gearbox material before and after fatigue fracture. The large pores are numbered from 1 to 12, and the final fracture path is indicated by the black dashed line in the post-fracture image. The fracture plane passes through the region between pores 9 and 10, which are both located close to the free surface and have relatively large coupling factors.
During fatigue cycling, I observed multiple crack initiation sites, primarily associated with the large pores. However, not all large pores contributed equally to the final failure. Pore 10, which has the largest coupling factor, initiated the main crack that propagated across the specimen. Pore 9, with a coupling factor of 2.55, also exhibited significant crack growth, but its crack remained secondary. The crack growth behavior from pores 9 and 10 is shown in the two-dimensional slices at 0, 6000, 8000, and 10,000 cycles. The cracks initiated at the pore surfaces and propagated in a direction roughly perpendicular to the loading axis. I observed local acceleration and deceleration of crack growth. The local acceleration is caused by the presence of secondary phase particles or smaller pores ahead of the crack tip, while the local deceleration is likely due to crack closure induced by plasticity at the crack tip. The KAM EBSD map confirmed that the grain boundaries and particle interfaces are preferential sites for dislocation accumulation, which can act as micro-crack nucleation sites.
To quantify the fatigue crack growth rate from each pore, I used two approaches. In the two-dimensional approach, the crack growth rate is defined by the increase in projected pore area:
\[
\frac{da}{dN} = \frac{\sqrt{a_n} – \sqrt{a_0}}{N},
\]
where \(a_n\) is the projected pore area after \(N\) cycles and \(a_0\) is the initial projected area. In the three-dimensional approach, I used the increase in pore volume:
\[
\frac{da}{dN} = \frac{\sqrt[3]{V_n} – \sqrt[3]{V_0}}{N},
\]
where \(V_n\) and \(V_0\) are the pore volumes after and before cycling, respectively. Both approaches gave similar trends. Table 4 summarizes the measured crack growth rates for the twelve large pores using the three-dimensional volume method.
| Pore no. | \(f\) | \(da/dN\) (×10⁻⁴ μm/cycle) |
|---|---|---|
| 1 | 17.94 | 2.00 |
| 2 | 0.31 | 0.64 |
| 3 | 4.86 | 1.42 |
| 4 | 0.86 | 0.39 |
| 5 | 0.26 | 0.45 |
| 6 | 0.41 | 0.27 |
| 7 | 1.97 | 0.83 |
| 8 | 0.21 | 0.18 |
| 9 | 2.55 | 0.98 |
| 10 | 24.09 | 2.43 |
| 11 | 0.18 | 0.12 |
| 12 | 0.57 | 0.32 |
I found that the fatigue crack growth rate from a given pore increases with increasing coupling factor \(f\). In fact, the relationship can be approximated by a linear function in the double-logarithmic domain. When \(f < 2\), the pore does not produce an observable crack within 10,000 cycles, whereas when \(f > 2\), the crack growth rate increases significantly. This threshold behavior is consistent with the idea that a pore must be sufficiently large and sufficiently close to the surface to generate a stress intensity factor high enough to drive crack growth. The crack growth rate from pore 10, which is the most threatening pore according to the coupling factor, is more than an order of magnitude higher than that from pore 8, which has the smallest coupling factor.
I also compared the crack growth rate with the pore volume and with the offset distance separately. As shown in the figures, there is no monotonic relationship between pore size and crack growth rate. For example, pores 4 and 6 have large radii of 136 μm and 119 μm, respectively, but their crack growth rates are only 0.39 and 0.27 ×10⁻⁴ μm/cycle, because they are located deep inside the specimen (d = 158 μm and d = 291 μm). Conversely, pore 1 with a radius of 96 μm and d = 5.35 μm has a crack growth rate of 2.00 ×10⁻⁴ μm/cycle. This clearly demonstrates that pore size alone cannot predict the failure location. Similarly, the offset distance alone is insufficient, because a small pore close to the surface may have a lower crack growth rate than a larger pore slightly further away. Thus, the coupling of size and position, embodied in the factor \(f\), is the most relevant parameter for predicting which casting defect will lead to final failure.
Influence of Pore Morphology and Orientation
In addition to pore size and position, the geometric shape and orientation of pores can influence stress concentration. Two common measures are the roundness \(\psi\) and the aspect ratio \(\beta\). The roundness distribution shows that most pores are nearly spherical; however, larger pores tend to have lower roundness values, indicating more irregular and convoluted shapes. In the reconstructed images, several large pores exhibited surface undulations that resemble micro-cracks. These sharp features can produce high local stress concentration factors, potentially exceeding 20 for complex-shaped pores, whereas a spherical pore typically produces a stress concentration factor around 2 to 3. Nevertheless, my experimental observations show that the coupling factor \(f\) dominates the fatigue crack growth rate, regardless of pore shape. For example, pore 1 has a relatively high coupling factor (17.94) and a moderate roundness, and it indeed initiated a fast-growing crack. Pore 5, which has a very irregular shape and a large surface area, has a coupling factor of only 0.26 because it is located deep inside the specimen; accordingly, its crack growth rate is low.
The orientation of ellipsoidal pores also affects stress concentration. For an ellipsoidal pore, the stress concentration factor is higher when the major axis is perpendicular to the loading direction than when it is parallel to the loading direction. However, the aspect ratio distribution in the gearbox material is narrow: 88.7% of pores have aspect ratios below 2.0. The influence of orientation is therefore limited compared with the size and position effects. I found no significant correlation between the pore aspect ratio and the crack growth rate. This suggests that, for the casting defect populations present in this material, the most critical factors are indeed the pore size and the pore distance to the free surface, which are captured by the coupling factor \(f\).
To further investigate the effect of pore morphology, I performed finite element simulations using both ideal spherical pores and the actual reconstructed pore geometries. In the ideal spherical pore models, the stress concentration factor at the pore equator was computed for each of the twelve pore sizes and positions. Table 5 lists the maximum stress concentration factors (\(K_t\)) for the ideal pores. The \(K_t\) values range from 1.975 to 2.910. The highest value is obtained for pore 10 (2.910), which also has the largest coupling factor. The results confirm that, for spherical pores, the stress concentration factor increases as the pore approaches the free surface and as the pore size increases, consistent with the coupling factor concept.
| Pore no. | \(r\) (μm) | \(d\) (μm) | \(f\) | \(K_t\) (ideal) |
|---|---|---|---|---|
| 1 | 96 | 5.35 | 17.94 | 2.600 |
| 2 | 91 | 296.78 | 0.31 | 1.979 |
| 3 | 100 | 20.42 | 4.86 | 2.428 |
| 4 | 136 | 158.01 | 0.86 | 2.100 |
| 5 | 103 | 402.25 | 0.26 | 1.986 |
| 6 | 119 | 290.93 | 0.41 | 2.004 |
| 7 | 68 | 34.57 | 1.97 | 2.068 |
| 8 | 86 | 418.93 | 0.21 | 1.975 |
| 9 | 86 | 33.58 | 2.55 | 2.130 |
| 10 | 73 | 3.02 | 24.09 | 2.910 |
| 11 | 63 | 351.81 | 0.18 | 1.983 |
| 12 | 80 | 140.98 | 0.57 | 2.008 |
For the actual reconstructed pore geometries, the maximum local stress concentration factors are much higher than those of ideal spheres due to the sharp re-entrant corners and concave surfaces. Table 6 summarizes the maximum stress concentration factors for the actual pores. The values range from 4.232 to 17.378. The extremely high value (17.378) for pore 10 corresponds to its proximity to the surface and its irregular shape. However, I observed that the location of the maximum stress is not always the location where fatigue cracks actually initiate. In the fatigue tests, cracks nucleated on the pore surface along the plane perpendicular to the loading axis, but not necessarily at the point of maximum stress. This finding suggests that the local microstructure, particularly the distribution of brittle secondary phase particles and the orientation of the \(\alpha\)-Al dendrites, plays a role in selecting the crack initiation site. The stress concentration factor alone is therefore insufficient to predict fatigue initiation at a precise point, but the coupling factor \(f\) provides a reliable ranking of the pore threat level.
| Pore no. | \(f\) | Max \(K_t\) | Average \(K_t\) |
|---|---|---|---|
| 1 | 17.94 | 14.920 | 1.788 |
| 2 | 0.31 | 4.404 | 2.378 |
| 3 | 4.86 | 10.400 | 1.107 |
| 4 | 0.86 | 5.938 | 1.651 |
| 5 | 0.26 | 16.756 | 1.638 |
| 6 | 0.41 | 8.900 | 1.920 |
| 7 | 1.97 | 11.600 | 1.711 |
| 8 | 0.21 | 4.232 | 1.676 |
| 9 | 2.55 | — | — |
| 10 | 24.09 | 17.378 | 2.312 |
| 11 | 0.18 | — | — |
| 12 | 0.57 | 4.978 | 2.089 |
To correlate the finite element results with the fatigue crack growth rates, I calculated the average stress concentration factor along the crack initiation plane (the plane perpendicular to the loading axis that passes through the pore center). This average value is more representative of the driving force for crack growth because fatigue cracks propagate over a finite volume, and the local microstructure can redistribute the stress. Table 6 shows that the average \(K_t\) values are much lower than the maximum values and are not strongly correlated with the coupling factor. For instance, pore 2 has an average \(K_t\) of 2.378, which is higher than that of pore 10 (2.312), yet the crack growth rate from pore 10 is significantly higher. This discrepancy can be explained by the fact that the stress along the crack path is not the only parameter controlling fatigue crack growth; the size of the pore also determines the initial crack length and the crack driving force according to fracture mechanics. The coupling factor combines both size and stress concentration in a phenomenological manner, and therefore works well for ranking pore severity.
Coupling Coefficient and Its Practical Applications
The core outcome of my research is the coupling coefficient \(f\), which is defined as
\[
f = \frac{r}{d} \quad \text{or equivalently} \quad f = \frac{\left(\frac{3V}{4\pi}\right)^{1/3}}{d},
\]
where \(V\) is the pore volume and \(d\) is the offset distance from the pore center to the nearest free surface. This coefficient is dimensionless and can be easily computed from three-dimensional tomographic data. In the current study, I found a strong linear relationship between \(f\) and the fatigue crack growth rate for pores with \(f > 2\). For lower values of \(f\), pores do not contribute significant crack growth within the tested lifetime. Therefore, the coupling factor can be used as a threshold parameter for identifying harmful casting defects in high-speed train gearbox housings.
One practical application is the prediction of the fatigue failure location. By calculating \(f\) for all resolved pores in a component, the pore with the maximum \(f\) value is expected to be the fatigue crack initiation site that ultimately leads to failure. In the present specimens, the fatal crack originated from pore 10, which indeed had the largest \(f\) value (24.09). In another specimen, pore 1 had the largest \(f\) value and also produced the dominant crack. This suggests that the coupling factor can be used in quality control to reject castings that contain critical pores near the surface. However, there are some limitations. The coupling factor does not predict the fatigue life in terms of cycles, nor does it account for the detailed pore morphology. Further development may combine \(f\) with fatigue life models, such as the Kitagawa-Takahashi diagram or the Murakami approach, to estimate the fatigue limit based on the square root of the projected defect area. The coupling factor could serve as a weighting parameter to modify the equivalent defect size.
Another practical application is the establishment of allowable pore size limits based on pore location. Using the finite element model, I calculated the maximum allowable pore radius for a given offset distance that produces the same stress concentration factor as a reference pore. Figure 15 shows the relationship between the maximum allowed pore radius and the pore center depth below the gearbox surface. The gearbox wall thickness is 15 mm. The horizontal axis represents the location of the pore center along the wall-thickness direction, while the vertical axis is the maximum allowed pore radius. When the pore center is at the outer surface, the maximum allowed radius is 0.5 mm, following the current standard for gas pores in the gearbox. When the pore center coincides with the inner surface, the maximum allowed radius is 0.22 mm. At the mid-thickness (7.5 mm from the surface), the maximum radius can increase to 2.2 mm without exceeding the same stress concentration level. This result indicates that surface pores are much more detrimental than internal pores of the same size. The current casting standards, which apply a single pore size limit, may be overly conservative for internal pores and insufficiently strict for surface pores. The coupling factor offers a rational basis for developing location-dependent acceptance criteria for casting defects.
Moreover, the coupling factor can be extended to other manufacturing processes such as selective laser melting, where the defect population is characterized by smaller, more spherical pores. My ongoing research focuses on verifying the applicability of the coupling factor to additively manufactured aluminum alloys and to develop fatigue life prediction models that incorporate f as a parameter. The ultimate goal is to provide a simple, robust tool for the design and quality assurance of high-speed train gearbox housings, thereby improving the safety and reliability of high-speed trains.
Conclusions
In this thesis, I investigated the casting defect characteristics and fatigue fracture mechanisms of high-speed train gearbox materials using a combination of experimental characterization, synchrotron tomography, in-situ fatigue testing, and finite element analysis. The main conclusions are as follows:
(1) The gearbox material is an Al-7Si-0.4Mg cast aluminum alloy consisting of an \(\alpha\)-Al matrix, eutectic Si, Mg\(_2\)Si precipitates, and Fe-rich intermetallic particles. The secondary phase particles are mainly 1–4 μm in size and are unevenly distributed. The casting defect population includes gas pores and shrinkage cavities with radii up to 136 μm, randomly distributed in size, roundness, and aspect ratio.
(2) The fatigue crack initiation and final failure of the gearbox material are primarily controlled by the casting defect size and the defect position relative to the free surface. Neither pore size nor pore location alone can predict the failure location. The coupling factor \(f = r/d\), which combines both parameters, shows a strong linear correlation with the fatigue crack growth rate for pores with \(f > 2\). Cracks initiate preferentially at the pore with the largest \(f\) value.
(3) Pore geometry (roundness and aspect ratio) and pore orientation have a secondary influence on fatigue crack growth in this material. Although irregular pore shapes can create high local stress concentrations, the fatigue crack path is determined by the coupled size-position effect as well as by the local microstructure, such as the distribution of brittle particles.
(4) Finite element simulations of ideal spherical pores confirm that the stress concentration factor increases with the coupling factor \(f\). Simulations using actual pore geometries produce locally high stress concentrations, but the maximum stress location does not necessarily coincide with the crack initiation site. Therefore, the coupling factor \(f\) is a more reliable indicator than the maximum stress concentration factor for predicting the fatigue failure origin.
(5) The coupling factor can be used to establish location-dependent allowable pore sizes in gearbox castings. For the same stress concentration level, the permissible pore radius increases significantly with increasing distance from the free surface. Surface pores require much stricter size limits than internal pores. This finding can guide casting quality standards and contribute to the safe design and maintenance of high-speed train gearbox housings.
In summary, this research emphasizes the critical role of casting defect coupling effects in the fatigue performance of high-speed train gearbox materials. The proposed coupling factor provides a simple and effective parameter for identifying dangerous pores and predicting fatigue failure locations. Future work will focus on extending the coupling factor to fatigue life prediction and to other materials and manufacturing processes.