An Inverse Analysis-Based Optimal Selection of Cohesive Zone Model for Metallic Materials

Zhao, Guanghui; Li, Ju; Zhang, Y.X.; Zheng, Liancun; Yang, Chunhui

doi:10.1142/s1758825118500151

Cited by 14 publications

(3 citation statements)

References 38 publications

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“…To examine the influence of the TSL shape on the mechanical properties of the bonded interface of IGBT modules, three commonly used TSLs [ 41 ], namely, the bilinear law, the exponential law, and the polynomial law, are selected in this paper, as illustrated in Figure 3 . The bilinear law is available in ABAQUS 2021.…”

Section: Cohesive Zone Modelingmentioning

confidence: 99%

Using Machine Learning and Finite Element Analysis to Extract Traction-Separation Relations at Bonding Wire Interfaces of Insulated Gate Bipolar Transistor Modules

Zhao,

An,

Wang

et al. 2024

Materials

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For insulated gate bipolar transistor (IGBT) modules using wire bonding as the interconnection method, the main failure mechanism is cracking of the bonded interface. Studying the mechanical properties of the bonded interface is crucial for assessing the reliability of IGBT modules. In this paper, first, shear tests are conducted on the bonded interface to test the bonded interface’s strength. Then, finite element–cohesive zone modeling (FE-CZM) is established to describe the mechanical behavior of the bonded interface. A novel machine learning (ML) architecture integrating a convolutional neural network (CNN) and a long short-term memory (LSTM) network is used to identify the shape and parameters of the traction separation law (TSL) of the FE-CZM model accurately and efficiently. The CNN-LSTM architecture not only has excellent feature extraction and sequence-data-processing abilities but can also effectively address the long-term dependency problem. A total of 1800 sets of datasets are obtained based on numerical computations, and the CNN-LSTM architecture is trained with load–displacement (F–δ) curves as input parameters and TSL shapes and parameters as output parameters. The results show that the error rate of the model for TSL shape prediction is only 0.186%. The performance metric’s mean absolute percentage error (MAPE) is less than 3.5044% for all the predictions of the TSL parameters. Compared with separate CNN and LSTM architectures, the proposed CNN-LSTM-architecture approach exhibits obvious advantages in recognizing TSL shapes and parameters. A combination of the FE-CZM and ML methods in this paper provides a promising and effective solution for identifying the mechanical parameters of the bonded interfaces of IGBT modules.

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Section: Cohesive Zone Modelingmentioning

confidence: 99%

Using Machine Learning and Finite Element Analysis to Extract Traction-Separation Relations at Bonding Wire Interfaces of Insulated Gate Bipolar Transistor Modules

Zhao,

An,

Wang

et al. 2024

Materials

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“…They found that the fracture toughness of the specimen decreased with the increase of the hole size. Zhao et al [17] simulated the tensile fracture process of steel plates using five different models. The five models are bilinear, polynomial, trapezoidal, exponential, and Park-Paulino-Roesler models.…”

Section: Introductionmentioning

confidence: 99%

Simulation of crack growth for metal plates with holes based on cohesive zone model

Ma¹,

Song²,

Zhang³

et al. 2022

Mater. Res. Express

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Hole defects are very common in metal plates. The propagation of cracks in engineering structural members will be affected by the holes of the members, which will not only change the propagation direction of cracks, but also have the ability to limit the growth of cracks. Therefore, the study of material fracture crack propagation caused by the distribution of holes and other factors under loading conditions has become a problem that needs to be considered in structural design. The cohesive zone model(CZM) can effectively avoid the singularity problem of crack tip stress when simulating crack growth, and at the same time can clearly show the crack growth path. Based on exponential cohesive zone model, the finite element analysis of tensile test for metallic materials with hole defects was carried out. The crack propagation law under constant load was obtained. It was proved that CZM could simulate the crack propagation in metallic materials with holes more accurately. The influence of the pore size, shape, distribution on the crack propagation is discussed. The results show that the smaller the distance difference between holes, the greater the supporting reaction force. The smaller the radius of the hole, the higher the fracture toughness and the maximum supporting reaction force of the metal plate. And it also can be seen that as the number of holes increases, the maximum supporting reaction force and fracture toughness of the metal plate decrease. The use of staggered holes distribution has greater supporting force and better toughness. The research results of this paper provide a theoretical basis and reference for investigating the propagation and propagation of cracks in the process of damage and failure of materials and for structural design and performance evaluation of engineering materials.

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“…A few researches on DP failure were reported, for example, fatigue failures of DPs caused by vibration [2], erosion wear generated by drilling fluid containing debris [3], static fracture characteristics studied by a cohesive zone model [4]. The effects of impact loading on dynamics responses of DPs with cracks and their fracture failure were rarely studied.…”

Section: Introductionmentioning

confidence: 99%

Finite Element Analysis of Dynamic Fracture Behaviour of Drill Pipe Under Various Impact Loads

Zhao

Zhao²,

Zhang

et al. 2018

mech

Self Cite

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In this paper, finite element analysis is conducted to study dynamic responses of a defected drill pipe (DP) under impact loading encountered in working conditions. Longitudinal impact loading such as tensile, eccentric compressive and torsional impact loading and transverse collision loading are considered. A finite element model is firstly developed and validated, and then employed to evaluate the effects of various impact loading on dynamic responses of the defected DP. It is found that the inertial effect due to tensile impact is the most prominent among all the longitudinal impact loadings. In addition, the effect of the transverse collision between the DP and the borehole wall on the driving force of the crack is evaluated. It is concluded that the dynamic effects of the various impact loading frequently exerting on the DP should be taken into consideration for life prediction of DPs. DOI: http://dx.doi.org/10.5755/j01.mech.24.4.19503

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An Inverse Analysis-Based Optimal Selection of Cohesive Zone Model for Metallic Materials

Cited by 14 publications

References 38 publications

Using Machine Learning and Finite Element Analysis to Extract Traction-Separation Relations at Bonding Wire Interfaces of Insulated Gate Bipolar Transistor Modules

Using Machine Learning and Finite Element Analysis to Extract Traction-Separation Relations at Bonding Wire Interfaces of Insulated Gate Bipolar Transistor Modules

Simulation of crack growth for metal plates with holes based on cohesive zone model

Finite Element Analysis of Dynamic Fracture Behaviour of Drill Pipe Under Various Impact Loads

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