Additive manufacturing (AM) has expanded significantly, particularly in aerospace; however, AM materials often have defects that impair fatigue performance. This study examines the geometry and morphology of critical defects in Ti-6Al-4V specimens produced using three printing quality settings, followed by hot isostatic pressing (HIP) or heat treatment (HT). We present an automated fatigue failure analysis framework using computer vision and AI to identify critical defects, measure surface proximity, and quantify 14 geometric and morphological features. The model achieved a mean IoU of 0.836 and approximately 10% error in feature measurement. Results show that surface proximity is the most influential factor on fatigue life, with near-surface defects degrading performance for HT specimens with lack-of-fusion (LOF) defects. For HIP specimens, failure sources were typically within 0.16-0.6 mm from the surface. Additionally, for LOF defects, the -parameter model achieved with measured cycles to failure.

Recently, there has been an increased interest in additive manufacturing (AM) for its potential to reduce costs and lighten the weight of manufactured parts. However, materials produced through AM are prone to defects that can significantly impact their fatigue resistance. Identifying fatigue failure sources is crucial for the characterization of critical manufacturing defects, especially for the future use of AM in main load-bearing structural parts. This requires conducting fatigue tests and manually inspecting fracture surfaces. In this research, we introduce an innovative machine-learning model designed to detect the initiation defects causing fatigue cracks in Titanium Ti-6Al-4V samples manufactured by selective laser melting (SLM). The model also measures the distance between the detected fatigue failure source and the surface of the material. Our approach involves initially segmenting out areas without initiation points, and then identifying these points in the remaining areas. We then use established computer vision techniques to calculate their distance from the surface. The results of our study highlight the significant potential of using machine learning and computer vision to automate fractographic analysis. This advancement could greatly improve the speed and efficiency of this process, marking a new phase of productivity in the field. This research not only furthers artificial intelligence by introducing an innovative method but also may possess important applications in engineering.

Additive manufacturing (AM) refers to advanced technologies for building 3D objects by adding material layer upon layer using either electron beam melting (EBM) or selective laser melting. AM allows us to produce lighter and more complex parts. However, various defects are created during the AM process, which severely affect fatigue behavior. In the current research, the effects of the anisotropic microstructure in the in-plane and out-of-plane orientations and defects on the fatigue crack propagation rate (FCPR) and crack path were studied. A resonance machine was used to determine the fatigue crack propagation rate (da/dN vs. ΔK) from the near-threshold up to the final fracture, accompanied by in situ Acoustic Emission (AE) monitoring. Micro-Computerized Tomography (µCT) enabled us to characterize surface and microstructural defects. Metallography was used to determine the microstructure vs. orientations and fractography to classify the fatigue fracture propagation modes. Calculations of the local stress distribution were performed to determine the interactions of the cracks with the defects. In the out-of-plane direction, the material exhibited high fatigue fracture toughness accompanied by a slightly lower fatigue crack propagation rate as compared to in-plane orientations. The near-threshold stress intensity factor was slightly higher in the out-of-plane orientation as compared to that in the in-plane one, accompanied by a lower exponent of the Paris law regime. The threshold decreased with an increasing load ratio as expected for both orientations. The crack propagation direction that crosses the elongated grains plays an important role in increasing fatigue resistance in the out-of-plane direction. In the in-plane directions, the crack propagates parallel to the grain boundary, interacts with more defects and exhibits more brittle striations on the fracture surface, resulting in lower fatigue resistance.

In this investigation, three subjects are considered. First, the effect of the human factor is examined. In carrying out analyses of fatigue delamination propagation tests on laminate composites, the delamination length must be measured. The human effect on measurement of the delamination length a by different investigators is discussed. A limited influence of the human factor on the measurement of the delamination length a, as well as on delamination propagation rate da=dN, is observed in this study. Secondly, the paper proceeds to discuss the influence of the R-ratio on the fatigue delamination growth rate. It is found that a higher rate of crack/delamination propagation is associated with lower R-ratios which appears to contradict conventional wisdom. This behavior is confirmed in tests. Thirdly, a comparison between the fatigue propagation rates of two material systems is considered. It is concluded that the energy release rate used to assess these materials should not be normalized.

In this investigation nearly mode II initiation and resistance energy release rate values, required for delamination propagation, were determined based on quasi-static calibrated end loaded split (C-ELS) fracture tests. Two multi-directional (MD) carbon fiber reinforced polymer (CFRP) material systems were examined. The first was manufactured as a wet-layup, with an initial delamination between a unidirectional ply and a plain woven ply. The second was manufactured from a prepreg, with an initial delamination along an interface between two plain woven plies oriented differently. Two-dimensional finite element analyses (FEAs) of the tested specimens were performed. Based upon the FEA results, with use of the displacement extrapolation (DE) method, as well as the virtual crack closure technique (VCCT), stress intensity factors were calculated. The obtained values were used to determine the in-plane mixed-mode phase angle for each test, which indicated nearly mode II deformation. Fracture toughness resistance curves or R-curves were generated as a function of the delamination extension. The critical initiation and resistance energy release rate values were obtained from the stress intensity factors, as well as with the J-integral, which are local methods. In addition, the global experimental compliance method (ECM) was used. Small differences were observed between the results obtained by means of the two methods. From a comparison between the R-curves of the two material systems, it was seen that the initiation energy release rate values were higher for the prepreg by 25.5%. A greater difference was found in the increasing portion of the R-curves, as well as the steady state energy release rate values.

Several two- and three-dimensional mixed-mode interface failure criteria are proposed for predicting delamination failure in multidirectional, laminate composites. The proposed criteria, based on the stress intensity factors K-1, K-2, and K-III, as well as the critical interface energy release rate G(ic) and phase angles. and., are examined using results obtained from Brazilian disk mixed-mode fracture toughness tests. Two material systems are considered. The first contains a delamination along an interface between a unidirectional fabric and a plain woven fabric. The second is composed of a plain woven fabric with fibers oriented in different directions in succeeding plies. The former was manufactured by means of a wet-layup and the latter is a prepreg. Finally, a statistical analysis is carried out to obtain a failure curve or surface with a 10% probability of unexpected failure and a 95% confidence. These curves or surfaces may be used to predict failure of structures containing these laminates and to assist in composite design.

Quasi-static tests were carried out on calibrated end loaded split (C-ELS) specimens to determine a critical initiation interface energy release rate or fracture toughness Gic. A multi-directional (MD) carbon fiber reinforced polymer (CFRP) laminate with a delamination between a unidirectional (UD) fabric ply with fibers oriented mainly in the 0°- direction and a plain balanced woven ply with tows oriented in the +45°/ - 45°- directions was considered. The Gic values from the non-precracked (NPC) specimens containing an artificial delamination were evaluated by means of an experimental compliance method (ECM), a beam theory (BT) method, as well as a two-dimensional finite element analysis (FEA) together with the area J-integral. In addition, the displacement extrapolation (DE) method and the virtual crack closure technique (VCCT) were used to determine the stress intensity factors Km (m = 1, 2) for each test. The stress intensity factors were normalized with a length scale L^ = 100 µm and used to calculate the phase angle ψ^. Finally, the obtained results were compared to critical initiation values which were obtained in a previous study from Brazilian disk (BD) tests for the same material and interface. The Gic value is a necessary property for predicting propagation of a delamination along the investigated interface. The aim of this paper is to examine the differences which occur as a result of using various methods to determine this value. Work is in progress to determine fracture resistance curves or R-curves. These curves relate the energy required for a delamination to propagate GR to the delamination extension Δa and may be used to predict the delamination resistance to propagation.

Twenty-seven mixed mode Brazilian disk specimens were tested to obtain the fracture toughness of a delamination between two fiber reinforced composite plies in a multi-directional laminate, manufactured by means of a wet-layup. Using finite element analyses and conservative integrals, mechanical and residual curing stress intensity factors were found and used to calculate the interface energy release rate and phase angles. Based on these results, a three-dimensional failure criterion is proposed to obtain a failure surface. This criterion may be used to predict failure of a structure containing this material and interface.

Fracture toughness tests using the Brazilian disk specimen (BD) were carried out to determine the toughness properties of a delamination between two fiber reinforced composite plies. The upper ply is a transversely isotropic UD fabric with fibers oriented in the 0-direction and the lower ply is a tetragonal plain balanced weave with fibers oriented in the +45°/ - 45°-directions. The composite is manufactured as a wet-layup. With the BD specimen, mixed mode combinations are achieved by changing the loading angle ω, between the load line and the delamination. Eight specimens were tested at four loading angles, two for each angle. Based on the test results, finite element (FE) analyses were carried out in conjunction with two methods, the three-dimensional conservative M-integral and displacement extrapolation (DE) to obtain the stress intensity factors along the delamination front for each specimen resulting from mechanical loads, as well as residual stresses. The two methods were used in order to validate the results. Both methods were extended for this specific interface and made use of the first term of the asymptotic solution of the displacement field. The stress intensity factors were superposed, and the critical interface energy release rates and phase angles were calculated and plotted.

The cusps of native aortic valve (AV) are composed of collagen bundles embedded in soft tissue, creating a heterogenic tissue with asymmetric alignment in each cusp. This study compares native collagen fiber networks (CFNs) with a goal to better understand their influence on stress distribution and valve kinematics. Images of CFNs from five porcine tricuspid AVs are analyzed and fluid-structure interaction models are generated based on them. Although the valves had similar overall kinematics, the CFNs had distinctive influence on local mechanics. The regions with dilute CFN are more prone to damage since they are subjected to higher stress magnitudes.

Calcific aortic valve disease (CAVD) is a progressive pathology characterized by calcification mainly within the cusps of the aortic valve (AV). As CAVD advances, the blood flow and associated hemodynamics are severely altered, thus influencing the mechanical performance of the AV. This study proposes a new method, termed reverse calcification technique (RCT) capable of re-creating the different calcification growth stages. The RCT is based on three-dimensional (3D) spatial computed tomography (CT) distributions of the calcification density from patient-specific scans. By repeatedly subtracting the calcification voxels with the lowest Hounsfield unit (HU), only high calcification density volume is presented. RCT posits that this volume re-creation represents earlier calcification stages and may help identify CAVD initiation sites. The technique has been applied to scans from 12 patients (36 cusps) with severe aortic stenosis who underwent CT before transcatheter aortic valve implantation (TAVI). Four typical calcification geometries and growth patterns were identified. Finite elements (FE) analysis was applied to compare healthy AV structural response with two selected CAVD-RCT configurations. The orifice area decreased from 2.9 cm2 for the healthy valve to 1.4 cm2 for the moderate stenosis case. Local maximum strain magnitude of 0.24 was found on the edges of the calcification compared to 0.17 in the healthy AV, suggesting a direct relation between strain concentration and calcification geometries. The RCT may help predict CAVD progression in patients at early stages of the disease. The RCT allows a realistic FE mechanical simulation and performance of calcified AVs.