Uncertainty Analysis in Fatigue Life Prediction of Concrete Using Evidence Theory

2016 ◽  
Vol 866 ◽  
pp. 25-30
Author(s):  
He Sheng Tang ◽  
Jia He Mei ◽  
Wei Chen ◽  
Da Wei Li ◽  
Song Tao Xue
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Uncertainty Analysis ◽  
Model Uncertainty ◽  
Life Prediction ◽  
Epistemic Uncertainty ◽  
Uncertainty Propagation ◽  
Evidence Theory ◽  
Fatigue Life Prediction ◽  
Theory Method

Various sources of uncertainty exist in concrete fatigue life prediction, such as variability in loading conditions, material parameters, experimental data and model uncertainty. In this article, the uncertainty model of concrete fatigue life prediction based on the S-N curve is built, and the evidence theory method is presented for uncertainty analysis in fatigue life prediction of concrete while considering the epistemic uncertainty of the parameter of the model. Based on the experimental of concrete four-point bending beams, the evidence theory method is applied to quantify the epistemic uncertainty stem from experimental data and model uncertainty. To improve the efficiency of computation, a method of differential evolution is adopted to speedup the works of uncertainty propagation. The efficiency and feasibility of the proposed approach are verified through a comparative analysis of probability theory.

Rapid Characterization of Fatigue Performance With Application to Additive Manufactured Components

2020 ◽  
Author(s):  
Dino A. Celli ◽  
M.-H. Herman Shen ◽  
Onome E. Scott-Emuakpor ◽  
Tommy J. George
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Life Prediction ◽  
Prediction Method ◽  
Experimental Tests ◽  
Parameter Selection ◽  
Process Parameter ◽  
Fatigue Life Prediction ◽  
Fatigue Performance ◽  
Cycles To Failure

Abstract The aim of this paper is to provide a fatigue life prediction method which can concurrently approximate both SN behavior as well as the inherent variability of fatigue efficiently with a limited number of experimental tests. The purpose of such a tool is for the quality assessment and verification of components using Additive Manufacturing (AM) processes and other materials with a limited knowledgebase. Interest in AM technology is continually growing in many industries, such as aerospace, automotive, or biomedical. But components often result in highly variable fatigue performance. The determination of optimal process parameters for the build process can be an extensive and costly endeavor due to either a limited knowledgebase or proprietary restrictions. Quantifying the significant variability of fatigue performance in AM components is a challenging task as there are many causes including machine to machine differences, recycles of powder, and process parameter selection. Therefore, a life prediction method which can rapidly determine the fatigue performance of a material with little or no prior information of the material and a limited number of experimental tests is developed as an aid in process parameter selection and fatigue performance qualification. This is performed by using a previously developed and simplistic energy based fatigue life prediction method, or Two Point method, to predict the inherent variability associated with fatigue performance. The proposed approach is verified by using predicted distributions of stress and cycles to failure and comparing with experimental data at 104 and 106 cycles to failure. SN life prediction is modeled via a modified Random Fatigue Limit (RFL) model where the two RFL model parameters are evaluated using Bayesian statistical inference and stochastic sampling techniques for distribution estimation. This is performed in a dynamic way such that the life prediction model is continually updated with the generation of experimental data.

scholarly journals A Modified Nonlinear Damage Accumulation Model for Fatigue Life Prediction Considering Load Interaction Effects

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Huiying Gao ◽  
Hong-Zhong Huang ◽  
Shun-Peng Zhu ◽  
Yan-Feng Li ◽  
Rong Yuan
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Life Prediction ◽  
Damage Accumulation ◽  
Interaction Effects ◽  
Fatigue Life Prediction ◽  
Accumulation Model ◽  
Proposed Model ◽  
Fatigue Damage Accumulation ◽  
Damage Accumulation Model

Many structures are subjected to variable amplitude loading in engineering practice. The foundation of fatigue life prediction under variable amplitude loading is how to deal with the fatigue damage accumulation. A nonlinear fatigue damage accumulation model to consider the effects of load sequences was proposed in earlier literature, but the model cannot consider the load interaction effects, and sometimes it makes a major error. A modified nonlinear damage accumulation model is proposed in this paper to account for the load interaction effects. Experimental data of two metallic materials are used to validate the proposed model. The agreement between the model prediction and experimental data is observed, and the predictions by proposed model are more possibly in accordance with experimental data than that by primary model and Miner’s rule. Comparison between the predicted cumulative damage by the proposed model and an existing model shows that the proposed model predictions can meet the accuracy requirement of the engineering project and it can be used to predict the fatigue life of welded aluminum alloy joint of Electric Multiple Units (EMU); meanwhile, the accuracy of approximation can be obtained from the proposed model though more simple computing process and less material parameters calling for extensive testing than the existing model.

scholarly journals A new type of S-N equation and its application to multiaxial fatigue life prediction

2021 ◽  
Author(s):  
xiangqiao yan
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Life Prediction ◽  
Multiaxial Fatigue ◽  
Fatigue Life Prediction ◽  
Metallic Materials ◽  
Material Constants ◽  
Numerical Fitting ◽  
Fatigue Model ◽  
New Type

The S-N equation is one of the most important equations in fatigue model investigation. A majority of fatigue models, including multiaxial fatigue model and mean effect models, are established on the basis of the S-N equation. Obviously, an accuracy of the S-N equation is very important. Taking into account that the S-N equation is, in fact, an empirical one in which the material constants are determined by numerical fitting fatigue experimental data, in this paper, the S-N equation can be improved, by further processing these fatigue experimental data, to present a new type of S-N equation that is more accurate than the S-N equation. The new type of S-N equation is called a similar S-N equation in this paper. By using a large number of experimental data of metallic materials reported in literature, an accuracy of the similar S-N equation has been proven.

Algorithms for multiaxial cycle counting method and fatigue life prediction based on the weight function critical plane under random loading

2019 ◽  
Vol 28 (9) ◽  
pp. 1367-1392 ◽  
Author(s):  
Xiao-Wei Wang ◽  
De-Guang Shang ◽  
Yu-Juan Sun ◽  
Xiao-Dong Liu
Keyword(s):  
Experimental Data ◽  
Aluminum Alloy ◽  
Fatigue Life ◽  
Weight Function ◽  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Fatigue Life Prediction ◽  
Counting Method ◽  
Critical Plane ◽  
Random Loading

Based on the critical plane determined by the weight function method, two algorithms for multiaxial cycle counting method are proposed by modifying the rainflow and range cycle counting methods. The proposed two algorithms can be applied to multiaxial random loading, and be suitable to any critical plane-based fatigue life prediction models, since the counted cycles or reversals are represented by the start time and end time. The proposed two algorithms are used to predict multiaxial fatigue life by the experimental data of 7075-T651 aluminum alloy, En15R steel and 7050-T7451 aluminum alloy conducted under multiaxial random loading in both high-cycle and low-cycle fatigue region. The life prediction results are in good agreement with the experimental data.

Mean Stress and Ratcheting Corrections in Fatigue Life Prediction of Metals

2016 ◽  
Vol 853 ◽  
pp. 57-61
Author(s):  
Qiang Lei ◽  
Peng Yue ◽  
Qiang Liu ◽  
Shun Peng Zhu ◽  
Hong Zhong Huang
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Model Prediction ◽  
Life Prediction ◽  
Inelastic Strain ◽  
Fatigue Life Prediction ◽  
Mean Stress ◽  
New Model ◽  
Proposed Model ◽  
Progressive Accumulation

Considering the effects of mean stress, the progressive accumulation inelastic strain occurs in engineering components under the direction of mean stress, it is simply known as ratcheting. Based on the ductility exhaustion theory, a new model is proposed to account for the effects of mean stress and ratcheting on the component fatigue life. The capability and accuracy of the proposed model are compared with those of Walker, Xia-Ellyin, Goswami, GDP and Peng models. A comparison between the model prediction and tested life is found to be quite satisfactory in the cases of 9 sets of experimental data available in the literature under different loading conditions.

Total fatigue life prediction for welded joints based on initial and equivalent crack size determination

2017 ◽  
Vol 27 (7) ◽  
pp. 1084-1104 ◽  
Author(s):  
Xiaoqiang Zhang ◽  
Huiying Gao ◽  
Hong-Zhong Huang
Keyword(s):  
Fatigue Life ◽  
Welded Joints ◽  
Model Uncertainty ◽  
Life Prediction ◽  
Crack Size ◽  
Initial Crack ◽  
Calculation Model ◽  
Fatigue Life Prediction ◽  
Random Loading ◽  
Calculation Process

When the linear elastic fracture mechanics-based approaches are used to predict the fatigue life of welded joints, initial crack size is a key point, which eventually affects the accuracy of total fatigue life prediction. Meanwhile, the life prediction process under random loading is complicated. In this paper, a novel method is proposed to determine the initial crack size, which is based on the results of back-extrapolation approach. The proposed method expresses the stress intensity factor, and the boundary between crack initiation and propagation period is taken into consideration. Based on the proposed method, deterministic total fatigue life can be obtained with fewer tests and less cost. In addition, the concept of equivalent crack size and its calculation model are proposed to reduce the complexity of the calculation process of fatigue life prediction under random loading, and model uncertainty is included into the prediction model of probabilistic fatigue life based on equivalent crack size. It is feasible, which has been verified, to take the influence of stress level into account when determining the initial crack size. Meanwhile, the proposal of equivalent crack size simplifies the calculation process of probabilistic fatigue life, and the consideration of model uncertainty is more conducive to assess the safety and reliability of the materials or structures.

scholarly journals Prediction of Fatigue Life of Welded Joints Made of Fine-Grained Martensite-Bainitic S960QL Steel and Determination of Crack Origins

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Tomasz Ślęzak
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Welded Joints ◽  
Life Prediction ◽  
Notch Root ◽  
Fatigue Cracks ◽  
Strain Range ◽  
Carbon Steels ◽  
Fatigue Life Prediction ◽  
The Impact

Due to growing requirements connected with the utilization of advanced structures, nowadays the modern design processes are developed. One of the crucial issues considered in these processes is proper design of the joints against fatigue in order to fulfill a stated life of operation. In this study, the method of fatigue life prediction based on the criterion of permissible strain range in the notch root is presented. An engaged simplified model of fatigue life prediction was previously developed for mild and carbon steels. The evaluation made during the research has proven that this method can also be used for S960QL high-strength steel characterized by entirely different properties and structure. A considered theoretical model demonstrates satisfactory correlation with experimental data and safely describes the fatigue life of weldments. Furthermore, the predicted fatigue life of studied steel without welds shows great comparability with experimental data. The limit value of the strain range in the notch root was estimated. Below this value of strain, the fatigue life of welded joints is infinite, theoretically. Finally, the impact of the surface imperfections on the fatigue crack initiation was revealed. For paternal material, the origins of cracking were discovered at the places of nonmetallic scale particles. In welded joints, the fatigue cracks initiated at the whole length of the fusion line.

scholarly journals Fatigue life prediction method for notched 3D woven composites based on progressive damage and field intensity

2020 ◽  
Vol 15 ◽  
pp. 155892502097832
Author(s):  
Jiaming Xue ◽  
Weidong Wen ◽  
Haitao Cui
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Fatigue Damage ◽  
Field Intensity ◽  
Life Prediction ◽  
Prediction Method ◽  
Fatigue Life Prediction ◽  
Woven Composites ◽  
Progressive Damage ◽  
3D Woven Composites

To solve the problem of fatigue life prediction of notched 3D woven composites, a novel fatigue life prediction method based on progressive damage and field intensity theory is proposed. By analyzing the initial loading process of 3D woven composite structure based on progressive damage method, the stress field when the fatigue damage develops gently and the dangerous area where the fatigue damage occurs first are obtained. Then combining with the concept of notch field intensity function, the failure criteria of composites and the three-dimensional space vector stress field intensity method, the fatigue damage degree field intensity of the fiber yarns in the dangerous area is analyzed and the most damaged fiber yarn is found. The fatigue life of the structure is calculated with the field intensity equivalent stress and the S-N curve of this fiber yarn. In order to verify the effectiveness of this method, the fatigue life of notched 3D woven composites under several stress levels is predicted and compared with the existing experimental data. The compared results show that the fatigue life prediction values are all within the two-fold error bounds of the experimental data, which are in good agreement with experimental results. Compared with the progressive damage fatigue life prediction method of woven composites, the prediction accuracy of the method proposed in this paper is improved by 31.5% on average, and the calculation efficiency is also greatly improved.

Probabilistic Life Prediction for High Temperature Low Cycle Fatigue Using Energy-Based Damage Parameter and Accounting for Model Uncertainty

2011 ◽  
Author(s):  
Shun-Peng Zhu ◽  
Hong-Zhong Huang ◽  
Victor Ontiveros ◽  
Li-Ping He ◽  
Mohammad Modarres
Keyword(s):  
Experimental Data ◽  
High Temperature ◽  
Fatigue Life ◽  
Model Uncertainty ◽  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Probabilistic Method ◽  
Damage Parameter ◽  
Probabilistic Methods ◽  
Cycle Fatigue

Probabilistic methods have been widely used to account for uncertainty from various sources to predict fatigue life for components or materials. The Bayesian approach can potentially give more accurate estimates by combining test data with technical knowledge available from theoretical analyses and/or previous experimental results. The aim of the present paper is to develop a probabilistic methodology for high temperature low cycle fatigue life prediction using an energy-based damage parameter and to demonstrate the use of an efficient probabilistic method. Accordingly, a Black-box approach is used to quantify model uncertainty for three damage parameters (the generalized damage parameter, SWT and plastic strain energy density (PSED)) using measured differences between experimental data and model predictions. The proposed model was verified using experimental data for nickel-base Superalloy GH4133 under different temperatures from literature. The results show that the uncertainty bounds using the generalized damage parameter for life prediction are tighter than that of SWT and PSED methods, which leads to better decision making based on the same available knowledge.

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