New ‘ηpl'' and ‘γ'' functions to evaluate J–R curve from cracked pipes and elbows. Part I: theoretical derivation

Experimental evaluation of J–R curve in a crack growth situation requires ‘η_pl' and ‘γ' functions that are specific to a cracked geometry and loading condition. All derivations of existing ‘η_pl' and ‘γ' functions are for specific cracked geometry and loading. In this paper, direct limit load based general equations of ‘η_pl' and ‘γ' functions have been derived. Subsequently, new ‘η_pl' and ‘γ' functions, which are not available in the literature, for pipe and elbow geometry with various crack configurations under different loading conditions have been derived. The derivations of ‘η_pl' and ‘γ' functions for throughwall circumferentially cracked elbow under in-plane bending moment uses the very recently proposed new limit load formulas.     

New ‘ηpl'' and ‘γ'' functions to evaluate J–R curve from cracked pipes and elbows. Part II: experimental and numerical validation

Experimental evaluation of J–R curve in a crack growth situation requires ‘η_pl' and ‘γ' functions that are specific to a cracked geometry and loading condition. In Part I [Engng. Fract. Mech., in press] of this paper, new η_pl and γ functions, which are not available in the literature, for pipe and elbow geometry with various crack configurations under different loading conditions have been derived. In this paper, some of these newly proposed η_pl and γ functions have been validated experimentally through comparison of crack initiation load and J–R curve. In few cases, numerical validation has also been provided by comparing the J-integral values calculated through η factor approach and finite element method.     

Damage evolution and real-time non-destructive evaluation of 2D carbon-fiber/SiC-matrix composites under fatigue loading

Electrical resistance acquisition, acoustic emission (AE) monitoring and infrared thermography were employed to evaluate damage evolution of 2D carbon-fiber/SiC-matrix composite under fatigue loading. Damage evolution was discussed on the basis of the calculation results of the modulus and mechanical hysteresis variation. At lower stress levels, the majority of damage was produced in the first few cycles and then the rate of damage accumulation gradually approached a steady value as the cycles proceeded. When the applied stress exceeded the endurance fatigue limit, extensive damage took place and led to failure of the composite. Changes of composite electrical resistance, AE activity and surface temperature had fairly well agreement with the modulus and hysteresis responses. It can be concluded that it is possible to employ these real-time non-destructive evaluation methods as in-situ damage evolution indicators for this kind of composites under fatigue loading.     

Prediction of J–R curves of thin-walled fuel pin specimens in a PLT setup

Recently, a Pin-Loading-Tension setup has evolved for evaluation of fracture behavior of thin-walled tubular specimens which are machined from nuclear reactor fuel pins. In this work, the geometric functions required for estimation of plastic component of J-integral from experimental load–load-line displacement data has been derived by carrying out a detailed 3D finite element analysis of the Pin-Loading-Tension test setup using the concept of limit load. The fracture resistance behavior (in terms of J–R curve) of the fuel pin specimens have been derived using: (a) multiple-specimen and (b) single specimen load-normalization technique.     

Factors determining the performance of thermoplastic polymer/wood composites; the limiting role of fiber fracture

Thermoplastic polymer/lignocellulosic fiber composites were prepared with a considerable range of matrices and fibers in an internal mixer. Tensile properties were determined on bars cut from compression molded plates. Local deformation processes initiated around the fibers were followed by acoustic emission testing supported by electron and polarization optical microscopy. The analysis of results proved that micromechanical deformation processes initiated by the fibers determine the performance of the composites. Debonding usually leads to the decrease of composite strength, but decreasing strength is not always associated with poor adhesion and debonding. The direction of property change with increasing wood content depends on component properties and interfacial adhesion. Good interfacial adhesion often results in the fracture of the fibers. Depending on their size and aspect ratio, fibers may fracture parallel or perpendicular to their axis. At good adhesion, the maximum strength achieved for a particular polymer/wood pair depends on the inherent strength of the fibers, which is larger for perpendicular than parallel fracture. Inherent fiber strength effective in a composite depends also on particle size, larger particles fail at smaller stress, because of the larger number of possible flaws in them. A very close correlation exists between the initiation stress of the dominating local deformation process and composite strength proving that these processes lead to the failure of the composite and determine its performance.     

An improved neural computing method for describing the scatter of S–N curves

The reliability evaluation of structural components under random loading is affected by several uncertainties. Proper statistical tools should be used to manage the large amount of causalities and the lack of knowledge on the actual reliability-affecting parameters. For fatigue reliability prediction of a structural component, the probability distribution of material fatigue resistance should be determined, given that the scatter of loading spectra is known and a suitable damage cumulating model is chosen. In the randomness of fatigue resistance of a material, constant amplitude fatigue test results show that at any stress level the fatigue life is a random variable. In this instance fatigue life is affected by a variety of influential factors, such as stress amplitude, mean stress, notch factor, temperature, etc. Therefore a hybrid neural computing method was proposed for describing the fatigue data trends and the statistical scatter of fatigue life under constant loading conditions for an arbitrary set of influential factors. To support the main idea, two examples are presented. It can be concluded that the improved neural computing method is suitable for describing the fatigue data trends and the scatter of fatigue life under constant loading conditions for an arbitrary set of influential factors, once the optimal neural network is designed and trained.