Crack Growth Analysis Using Ansys Software
Major Rowley
Hello, I am working on a fatigue crack growth analysis and have a problem when i try to use a smart crack growth option. Method: SMART keeps turning red. I have done the same simulation on the same object in 3D analysis and it worked fine, but when i switch to 2D this problem occurs.
Damage tolerant design relies on accurately predicting the growth rate and path of fatigue cracks under constant and variable amplitude loading. ANSYS Mechanical R19.2 was used to perform a numerical analysis of fatigue crack growth assuming a linear elastic and isotropic material subjected to constant amplitude loading. A novel feature termed Separating Morphing and Adaptive Remeshing Technology (SMART) was used in conjunction with the Unstructured Mesh Method (UMM) to accomplish this goal. For the modified compact tension specimen with a varied pre-crack location, the crack propagation path, stress intensity factors, and fatigue life cycles were predicted for various stress ratio values. The influence of stress ratio on fatigue life cycles and equivalent stress intensity factor was investigated for stress ratios ranging from 0 to 0.8. It was found that fatigue life and von Mises stress distribution are substantially influenced by the stress ratio. The von Mises stress decreased as the stress ratio increased, and the number of fatigue life cycles increased rapidly with the increasing stress ratio. Depending on the pre-crack position, the hole is the primary attraction for the propagation of fatigue cracks, and the crack may either curve its direction and grow towards it, or it might bypass the hole and propagate elsewhere. Experimental and numerical crack growth studies reported in the literature have validated the findings of this simulation in terms of crack propagation paths.
If the number of substeps is reduced, the analysis completes more quickly, but the accuracy of the thermal growth calculation is reduced. This is illustrated by the above analysis performed over only 5 substeps:
The procedure lets a large displacement solution with a sufficient number of substeps during any thermal ramped load predict thermal growths that results in substantial increases in the linear dimensions and volume of a body. Testing with a Workbench model illustrated that the mass density does not have to be adjusted as a function of temperature when volume changes result during an analysis.
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Hi, I am doing project on mixed mode crack growth of semi elliptical crack in gas turbine components under cyclic loading. Ansys has capability for finding J,K using CINT command. But, In mixed mode crack growth, i dont know how to deal with nodes and how to create random crack with new node coordinates obtained from previous steps. If you have any ansys code related to creating crack and finding fracture parameters like K, J (mode 1 or mixed mode), Can you please give me the code.
i m dan doing ME Engineering Design.I m doing project in the area of probabilistic fracture mechanics.,So i need how to find SIF,J integral,Energy release rate,CDOT for all type of crack (2D,3D)..,I want some of the material related to this..,i m using Ansys..,so complete step by step procedure in Crack analysis using analysis i want 3d Crack analysis
A finite element model of the spinal column including growth dynamics was utilized. The initial geometric models were constructed from the bi-planar radiographs of a normal subject. Based on this model, five other geometric models were generated to emulate different coronal and sagittal curves. The detailed modeling integrated vertebral body growth plates and growth modulation spinal biomechanics. Ten years of spinal growth was simulated using AIS and normal growth profiles. Sequential measures of spinal alignments were compared.
(1) Given the initial lateral deformity, the AIS growth profile induced a significant Cobb angle increase, which was roughly between three to five times larger compared to measures utilizing a normal growth profile. (2) Lateral deformities were absent in the models containing no initial coronal curvature. (3) The presence of a smaller kyphosis did not produce an increase lateral deformity on its own. (4) Significant reduction of the kyphosis was found in simulation results of AIS but not when using the growth profile of normal subjects.
The shape of a normal spine was used as an initial geometry and reconstructed from the bi-planar radiographs of a non-pathological female subject [24]. This geometric model is composed of 17 vertebral bodies from T1 to L5, and 16 intervertebral discs using published linear material properties (Table 1) [25]. Each vertebra was modeled as a wedged cylinder that consists of cortical and trabecular bone and three layers of the vertebral growth plates: the sensitive layer, the newly formed bone layer, and the transition layer [25, 26] (Figure 1). The intervertebral disc includes the annulus fibrosus and nucleus pulposus. In this modeling approach, the sensitive layer of the vertebral growth plate receives the stress used to determine the local bone growth rate. The newly formed bone layer is where new bone is simulated (bone calcification). The transition layer connects the sensitive and the newly formed bone layers to the completely formed bone. The complete model consisted of approximately 30,000 nodes and 40,000 elements.
The validity of the developed modeling platform to comply with scoliotic progression was explored using patient data. Three patients were selected with different curve types: Lenke type-1A, Lenke type-2A, and Lenke type-3C, with no significant alteration in sagittal spinal alignment i.e., kyphotic curves between 20 and 35 with less than 5 degrees modification over time. These patients previously underwent an annual radiographic follow up of 3, 2, and 2 years respectively. The formerly described simulation methods were performed utilizing regular adolescent growth rates (G m ) of 0.8 mm/year and 1.1 mm/year in thoracic and lumbar spines respectively [30]. Starting from initial patient curves, the model was constructed and its ability to corroborate with patient data was deemed successful if curve patterns were replicated within 5 degrees for the Cobb angles.
Based on initial geometry of the patient-specific model, five other spine geometries with different kyphosis angles and lateral curves were generated by varying the spatial orientations of the vertebral bodies and intervertebral discs (Figure 2). Based on these six geometrical models, the corresponding finite element models were generated. The variety of spinal configurations allowed a detailed analysis of the influence of varying growth profiles on spinal alignment.
Several steps were undertaken to ensure that the model corroborated with reality while behaving in a robust fashion. The growth algorithm utilized in this analysis was acquired from in-vivo experimentation [34] while its application utilizing finite element analysis to explore progressive scoliotic spines has previously been demonstrated [21, 23]. The longitudinal stresses measured in the intervertebral disc L5 showed agreement with in-vivo measurements [35]. Furthermore, in order to explore the influence of the adopted numerical assumptions on the results, several sensitivity analyses were performed. These additional simulations explored the influence of the selected growth constant (β = 0.4 to 0.6 MPa-1, a range of plausible physiologic values [36]), the loading configuration (gravitational and follower type spinal loading), and the magnitude of the growth velocities (G m = 15% of values reported in Figure 3).
However, when an initial coronal deformity was present, both AIS and normal growth profiles resulted in increased lateral deformity. This progressive trend was significantly amplified when using the AIS growth profile. More specifically, after ten years of simulated growth cases 3, 4, 5, and 6 underwent Cobb angle increases with magnitudes respectively measured at 5.0, 4.3, 5.2, and 3.4 times larger using AIS growth profile compared to the normal one.
The sensitivity analysis of β (0.4 to 0.6 MPa-1) magnified spinal Cobb angle amplitudes as β was increased. The final angle measures (after 10 years of simulated growth) were roughly doubled under a β of 0.6 compared to 0.4. However, relative differences between final measures of AIS and healthy growth rates remained as described above. That is, the relative increase in coronal Cobb (CobbAIS growth/Cobbnormal growth after 10 years of simulated growth), for cases 3 to 6, varied lightly between 1.85 to 2.61 and 1.79 to 2.86 when using a beta of 0.4 and 0.6 respectively. Therefore, it was consistently maintained that the AIS growth rate significantly encouraged additional scoliotic progression. Analysis of spinal loading (gravity force or sagittal plane follower load) also proved not to significantly alter the tendency of AIS growth to promote progression. To elaborate, the average Cobb angle increase initiated by the use of the AIS growth profile was between 1.85 to 2.61 and 1.50 to 1.88 when adopting gravity and sagittal follower loads respectively. Analysis of growth velocities (G m = 15%) altered magnitude of measured Cobb angles, to a lesser extent than factor β, and again, the relative comparisons were not significantly changed. More specifically, even when a 15% decrease in AIS growth rates was coupled with a 15% increase in normal growth velocities, final coronal Cobb angle related to AIS growth remained 1.8 times larger than that of the normal growth.
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