48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference · 2007 · 20 citations · 7 references
Natural SciencesMaterials EngineeringMaterials ScienceMechanical Behavior Of MaterialsMetallic MaterialsStructural EngineeringFracture MechanicsFracture ToughnessMechanical CharacterizationStrength Of MaterialsStress AnalysisStress-strain BehaviorCrack GrowthFatigue Crack GrowthFatigue LifeFatigue Life AssessmentFatigue Life PredictionStress-strain CurveStress-strain Curve AnalysisStructural Fatigue
In this paper, a new strategy for fatigue (S-N) and fatigue crack growth is proposed. It starts with estimation of the fracture toughness from simple tensile tests and ends up to the prediction of structural fatigue life. The methodology consists of three parts as shown in Figure 1. In Part I the information from a complete stress-strain curve was used to estimate the fracture toughness based on the energy method developed by Farahmand [1, 2]. As the result the GENOA/FTD module was developed for this functionality. The Fracture Toughness Determination code (FTD) is a useful tool that can generate the plane strain and plane stress fracture toughness for metallic alloys by using the material static properties. In addition, it can provide material fracture toughness as a function of part thickness. In Part II, the plane strain and plane stress fracture toughness (KIC & KC) were used to generate the fatigue crack growth rate data (the da/dN versus ∆K curve). The Fatigue Crack Growth module (GENOA/FCG) was established which can generate the whole region of the da/dN versus ∆K curve [3]. In Part III, the da/dN versus ∆K curve was used to predict the fatigue life and residual strength in conjunction with finite element analysis (FEA). When the stress intensity factor solution is not available for the crack geometry in consideration, the virtual crack closure technique (VCCT) was used to compute the strain energy release rates which were then converted to stress intensity factors [4-8]. The GENOA/PFA module, a progressive failure analysis code, has this functionality.
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Mary Kae Lockwood · Astrobiology · 2001 · 174 citations
De Xie, Sherrill B. Biggers · Engineering Fracture Mechanics · 2005 · 127 citations
Engineering, Computational Engineering, Materials Engineering +17