Nonlinear Response and Fatigue Life of Shallow Shells to Acoustic Excitation Using Finite Element

Author(s):  
Adam Przekop ◽  
Xinyun Guo ◽  
Salim Azzouz ◽  
Chuh Mei
Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 397
Author(s):  
Yahya Ali Fageehi

This paper presents computational modeling of a crack growth path under mixed-mode loadings in linear elastic materials and investigates the influence of a hole on both fatigue crack propagation and fatigue life when subjected to constant amplitude loading conditions. Though the crack propagation is inevitable, the simulation specified the crack propagation path such that the critical structure domain was not exceeded. ANSYS Mechanical APDL 19.2 was introduced with the aid of a new feature in ANSYS: Smart Crack growth technology. It predicts the propagation direction and subsequent fatigue life for structural components using the extended finite element method (XFEM). The Paris law model was used to evaluate the mixed-mode fatigue life for both a modified four-point bending beam and a cracked plate with three holes under the linear elastic fracture mechanics (LEFM) assumption. Precise estimates of the stress intensity factors (SIFs), the trajectory of crack growth, and the fatigue life by an incremental crack propagation analysis were recorded. The findings of this analysis are confirmed in published works in terms of crack propagation trajectories under mixed-mode loading conditions.


Polymers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 483
Author(s):  
Kazem Reza Kashyzadeh ◽  
Seyed Saeid Rahimian Koloor ◽  
Mostafa Omidi Bidgoli ◽  
Michal Petrů ◽  
Alireza Amiri Asfarjani

The main purpose of this research is to design a high-fatigue performance hoop wrapped compressed natural gas (CNG) composite cylinder. To this end, an optimization algorithm was presented as a combination of finite element simulation (FES) and response surface analysis (RSA). The geometrical model was prepared as a variable wall-thickness following the experimental measurements. Next, transient dynamic analysis was performed subjected to the refueling process, including the minimum and maximum internal pressures of 20 and 200 bar, respectively. The time histories of stress tensor components were extracted in the critical region. Furthermore, RSA was utilized to investigate the interaction effects of various polymer composite shell manufacturing process parameters (thickness and fiber angle) on the fatigue life of polymer composite CNG pressure tank (type-4). In the optimization procedure, four parameters including wall-thickness of the composite shell in three different sections of the CNG tank and fiber angle were considered as input variables. In addition, the maximum principal stress of the component was considered as the objective function. Eventually, the fatigue life of the polymer composite tank was calculated using stress-based failure criterion. The results indicated that the proposed new design (applying optimal parameters) leads to improve the fatigue life of the polymer composite tank with polyethylene liner about 2.4 times in comparison with the initial design.


2019 ◽  
Vol 893 ◽  
pp. 1-5 ◽  
Author(s):  
Eui Soo Kim

Pressure vessels are subjected to repeated loads during use and charging, which can causefine physical damage even in the elastic region. If the load is repeated under stress conditions belowthe yield strength, internal damage accumulates. Fatigue life evaluation of the structure of thepressure vessel using finite element analysis (FEA) is used to evaluate the life cycle of the structuraldesign based on finite element method (FEM) technology. This technique is more advanced thanfatigue life prediction that uses relational equations. This study describes fatigue analysis to predictthe fatigue life of a pressure vessel using stress data obtained from FEA. The life prediction results areuseful for improving the component design at a very early development stage. The fatigue life of thepressure vessel is calculated for each node on the model, and cumulative damage theory is used tocalculate the fatigue life. Then, the fatigue life is calculated from this information using the FEanalysis software ADINA and the fatigue life calculation program WINLIFE.


2001 ◽  
Vol 42 (5) ◽  
pp. 809-813 ◽  
Author(s):  
Young-Eui Shin ◽  
Kyung-Woo Lee ◽  
Kyong-Ho Chang ◽  
Seung-Boo Jung ◽  
Jae Pil Jung

Author(s):  
Zhenguo Lu ◽  
Lirong Wan ◽  
Qingliang Zeng ◽  
Xin Zhang ◽  
Kuidong Gao

Conical picks are the key cutting components used on roadheaders, and they are replaced frequently because of the bad working conditions. Picks did not meet the fatigue life when they were damaged by abrasion, so the pick fatigue life and strength are excessive. In the paper, in order to reduce the abrasion and save the materials, structure optimization was carried out. For static analysis and fatigue life prediction, the simulation program was proposed based on mathematical models to obtain the cutting resistance. Furthermore, the finite element models for static analysis and fatigue life analysis were proposed. The results indicated that fatigue life damage and strength failure of the cutting pick would never happen. Subsequently, the initial optimization model and the finite element model of picks were developed. According to the optimized results, a new type of pick was developed based on the working and installing conditions of the traditional pick. Finally, the previous analysis methods used for traditional methods were carried out again for the new type picks. The results show that new type of pick can satisfy the strength and fatigue life requirements.


2000 ◽  
Vol 123 (1) ◽  
pp. 150-154
Author(s):  
John H. Underwood ◽  
Michael J. Glennon

Laboratory fatigue life results are summarized from several test series of high-strength steel cannon breech closure assemblies pressurized by rapid application of hydraulic oil. The tests were performed to determine safe fatigue lives of high-pressure components at the breech end of the cannon and breech assembly. Careful reanalysis of the fatigue life tests provides data for stress and fatigue life models for breech components, over the following ranges of key parameters: 380–745 MPa cyclic internal pressure; 100–160 mm bore diameter cannon pressure vessels; 1040–1170 MPa yield strength A723 steel; no residual stress, shot peen residual stress, overload residual stress. Modeling of applied and residual stresses at the location of the fatigue failure site is performed by elastic-plastic finite element analysis using ABAQUS and by solid mechanics analysis. Shot peen and overload residual stresses are modeled by superposing typical or calculated residual stress distributions on the applied stresses. Overload residual stresses are obtained directly from the finite element model of the breech, with the breech overload applied to the model in the same way as with actual components. Modeling of the fatigue life of the components is based on the fatigue intensity factor concept of Underwood and Parker, a fracture mechanics description of life that accounts for residual stresses, material yield strength and initial defect size. The fatigue life model describes six test conditions in a stress versus life plot with an R2 correlation of 0.94, and shows significantly lower correlation when known variations in yield strength, stress concentration factor, or residual stress are not included in the model input, thus demonstrating the model sensitivity to these variables.


Author(s):  
Fei Song ◽  
Ke Li

Abstract In this paper, a hybrid computational framework that combines the state-of-the art machine learning algorithm (i.e., deep neural network) and nonlinear finite element analysis for efficient and accurate fatigue life prediction of rotary shouldered threaded connections is presented. Specifically, a large set of simulation data from nonlinear FEA, along with a small set of experimental data from full-scale fatigue tests, constitutes the dataset required for training and testing of a fast-loop predictive model that could cover most commonly used rotary shouldered connections. Feature engineering was first performed to explore the compressed feature space to be used to represent the data. An ensemble deep learning algorithm was then developed to learn the underlying pattern, and hyperparameter tuning techniques were employed to select the learning model that provides the best mapping, between the features and the fatigue strength of the connections. The resulting fatigue life predictions were found to agree favorably well with the experimental results from full-scale bending fatigue tests and field operational data. This newly developed hybrid modeling framework paves a new way to realtime predicting the remaining useful life of rotary shouldered threaded connections for prognostic health management of the drilling equipment.


Sign in / Sign up

Export Citation Format

Share Document