Prediction of stress-strain behaviors in steels using an integrated constitutive, FEM and ANN model

Austenitic steels with a carbon content of 0.0037 to 0.79 wt% C are torsion tested and modeled using a physically based constitutive model and an Integrated Phenomenological and Artificial neural Network (IPANN) model. The prediction of both the constitutive and IPANN models on steel 0.017 wt% C is then evaluated using a finite element (FEM) code ABAQUS with different reduction in the thickness after rolling through one roll stand. It is found that during the rolling process, the prediction accuracy of the reaction force from FEM simulation for both constitutive and IPANN models depends on the strain achieved (average reduction in thickness). By integrating FEM into IPANN model and introducing the product of strain and stress as an input of the ANN model, the accuracy of this integrated FEM and IPANN model is higher than either the constitutive or IPANN model.

Contact pressure and wear in sheet metal forming - an FEM analysis

Wear is the principal cause of tool failure in most sheet metal forming processes. It is well known that the contact pressure between the blank and the tool has a large influence on the wear of the tool, and hence the tool life. This investigation utilises the finite element method to analyse the contact pressure distribution over the die radius for a particular deep drawing process. Furthermore, the evolution of the predicted contact pressure distribution throughout the entire stroke of the punch is also examined. It was found that the majority of the process shows a steady state pressure distribution, with two characteristic peaks over the die radius, at the beginning and end of the sheet contact area. Interestingly, the initial transient contact pressure response showed extremely high localised peak pressures; more than twice that of the steady state peaks. Results are compared to wear reported in the literature, during similar experimental deep drawing processes. Finally, the significance and effect of the results on wear and wear-testing techniques are discussed.

Evaluation of effective material properties of composite materials using special FEM

In the present paper, a novel method using the special 2D finite element method (FEM) and the concept of equivalent homogeneous materials has been employed to evaluate the effective material properties of composites. Special 2D finite elements containing an internal defect or reinforcement have been well developed in order to greatly simplify the numerical modeling of composites. It can assure the high precision especially in the vicinity of defects or reinforcements in composite materials. Some numerical examples will be provided to demonstrate the validity and versatility of the proposed method by comparing the existing results from other literatures.

Damage identification of civil infrastructure in the time domain using FEM calibrated ARMAX model

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. First, a high quality finite element model is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then developed and calibrated. The calibrated ARMAX model can be used to identify damage in different scenarios through model updating process using clonal selection algorithm (CSA). The identification results demonstrate the performance of the proposed methodology, which has the potential to be used for damage identification in practices.

FEM calibrated ARMAX model updating method for time domain damage identification

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. To do this, a finite element model of a steel pipe laid on the soil is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then built and calibrated. The calibrated ARMAX model is used to identify different damage scenarios through model updating process using clonal selection algorithm (CSA). The results demonstrate the application potential of the proposed method in identifying the pipeline conditions. To further verify its performance, laboratory tests of a steel pipe laid on the soil with and without soil support (free span damage) are carried out. The identification results of pipe-soil system show that the proposed method is capable of identifying damagein a complex structural system. Therefore, it can be applied to identifying pipeline conditions.

Study on LiFe1 − xSm xPO4/C used as cathode materials for lithium-ion batteries with low Sm component

LiFe1 − xSmxPO4/C cathode materials were synthesized though a facile hydrothermal method. Compared with high-temperature solid-phase sintering, the method can allow for the fabrication of low Sm content (2 %), a scarce and expensive rare earth element, while the presence of an optimized carbon coating with large amount of sp²-type carbon sharply increases the material’s electrochemical performance. The high-rate dischargeability at 5 C, as well as the exchange current density, can be increased by 21 and 86 %, respectively, which were attributed to the fine size and the large cell parameter a/c as much. It should be pointed out that the a/c value will be increased for the LiFePO4 Sm-doped papered by both of the two methods, while the mechanism is different: The value c is increased for the front and the value a is decreased for the latter, respectively.