Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userA non-linear damage accumulation fatigue model for predicting strain life at variable amplitude loadings based on constant amplitude fatigue data
281
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
A new phenomenological technique for using constant amplitude loading data to predict fatigue life from a variable amplitude strain history is presented. A critical feature of this reversal-by-reversal model is that the damage accumulation is inherently non-linear. The damage for a reversal in the variable amplitude loading history is predicted by approximating that the accumulated damage comes from a constant amplitude loading that has the strain range of the particular variable amplitude reversal. A key feature of this approach is that overloads at the beginning of the strain history have a more substantial impact on the total lifetime than overloads applied toward the end of the cycle life. This technique effectively incorporates the strain history in the damage prediction and has the advantage over other methods in that there are no fitting parameters that require substantial experimental data. The model presented here is validated using experimental variable amplitude fatigue data for three different metals.
rate research
Read More
This paper presents a statistical framework enabling optimal sampling and robust analysis of fatigue data. We create protocols using Bayesian maximum entropy sampling, which build on the staircase and step methods, removing the requirement of prior knowledge of the fatigue strength distribution for data collection. Results show improved sampling efficiency and parameter estimation over the conventional approaches. Statistical methods for distinguishing between distribution types highlight the role of the protocol in model distinction. Experimental validation of the above work is performed, showing the applicability of the methods in laboratory testing.
The damage mechanisms and load redistribution of high strength TC17 titanium alloy/unidirectional SiC fibre composite (fibre diameter = 100 $mu$m) under high temperature (350 {deg}C) fatigue cycling have been investigated in situ using synchrotron X-ray computed tomography (CT) and X-ray diffraction (XRD) for high cycle fatigue (HCF) under different stress amplitudes. The three-dimensional morphology of the crack and fibre fractures has been mapped by CT. During stable growth, matrix cracking dominates with the crack deflecting (by 50-100 $mu$m in height) when bypassing bridging fibres. A small number of bridging fibres have fractured close to the matrix crack plane especially under relatively high stress amplitude cycling. Loading to the peak stress led to rapid crack growth accompanied by a burst of fibre fractures. Many of the fibre fractures occurred 50-300 $mu$m from the matrix crack plane during rapid growth, in contrast to that in the stable growth stage, leading to extensive fibre pull-out on the fracture surface. The changes in fibre loading, interfacial stress, and the extent of fibre-matrix debonding in the vicinity of the crack have been mapped for the fatigue cycle and after the rapid growth by high spatial resolution XRD. The fibre/matrix interfacial sliding extends up to 600 $mu$m (in the stable growth zone) or 700 $mu$m (in the rapid growth zone) either side of the crack plane. The direction of interfacial shear stress reverses with the loading cycle, with the maximum frictional sliding stress reaching ~55 MPa in both the stable growth and rapid growth regimes.
A new fatigue life prediction method using the energy-based approach under uniaxial and multiaxial random loadings is proposed in this paper. One unique characteristic of the proposed method is that it uses time-derivative damage accumulation model compared to the classical cycle-based damage accumulation model. Thus, damage under arbitrary random loading can be directly obtained using time-domain integration without cycle counting (e.g., rain-flow cycle counting method in classical fatigue analysis). First, a brief review of existing models is given focusing on their applicability to uniaxial/multiaxial, constant/random, and high cycle fatigue/low cycle fatigue loading regimes. It is observed that most existing models are only applicable to certain loading conditions and many of them are not applicable/validated under random loadings. Next, a time-derivative damage accumulation model under uniaxial random loading is proposed. The proposed damage function is inspired by a time-domain fatigue crack growth model. The fatigue life is obtained by integrating the damage function following random energy loading histories. Following this, an equivalent energy concept for general multiaxial loading conditions is used to convert the random multiaxial loading to an equivalent random uniaxial loading, where the time-derivative damage model can be used. Finally, the proposed model is validated with extensive experimental data from open literature and in-house testing data under various constant and random spectrum loadings. Conclusions and future work are suggested based on the findings from this study.
This work is focused on the micromechanical modelling of the low cycle fatigue of the nickel based $gamma/gamma$ superalloy AM1 at high temperature. The nature of the activated slip systems in the different types of channels of the $gamma$ phase is analysed, taking into account the combined effects of the applied and internal stresses. The latter are split into two contributions, misfit stresses and compatibility stresses between the elastic $gamma$ phase and the elasto-plastic $gamma$ phase, which are estimated within a simplified composite approach. Internal stresses may induce slip activity and/or be relaxed by it, which results in a complex sequence of slip activation events in the different channels under increasing applied stress. The consideration of these effects leads to a prediction of the nature and distribution of the active slip systems within the channels in [001] tension, compression and during low cycle fatigue. The resulting microstructural behaviour and its consequences regarding the anisotropic nature of the coalescence of the $gamma$ precipitates are discussed with respect to the available experimental data.
In the present study, a general probabilistic design framework is developed for cyclic fatigue life prediction of metallic hardware using methods that address uncertainty in experimental data and computational model. The methodology involves (i) fatigue test data conducted on coupons of Ti6Al4V material (ii) continuum damage mechanics based material constitutive models to simulate cyclic fatigue behavior of material (iii) variance-based global sensitivity analysis (iv) Bayesian framework for model calibration and uncertainty quantification and (v) computational life prediction and probabilistic design decision making under uncertainty. The outcomes of computational analyses using the experimental data prove the feasibility of the probabilistic design methods for model calibration in presence of incomplete and noisy data. Moreover, using probabilistic design methods result in assessment of reliability of fatigue life predicted by computational models.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
