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PE pipeline is widely used in urban gas pipe network. The carrying capacity of PE pipe with local thinning defects is an important means to ensure its safe operation.Firstly, the initial elastic modulus and yield stress are fitted by the finite element method to obtain the carrying capacity of internal pressure, bending moment and axial force, the BP neural network model including relative depth C/T, relative axial length 2A/√RT, relative circumferential angle 2θ/π and dimensionless parameters c, and combined with GA optimized BP neural network model. It can be found: the predicted value of the model is relatively consistent with the simulation results, which shows that the method of GA optimization of the BP neural network model is feasible,which provides an effective method for the intelligent safety evaluation of the PE pipeline with local thinning defects. [ABSTRACT FROM AUTHOR]

BACKGROUND: Human bones are characterized by strong nonlinearity and uneven bone distribution. Different elastic modulus assignments lead to great differences in static results. OBJECTIVE: To analyze differences of the three material attribute assigning methods in the numerical simulation analysis of vertebral body. METHODS: Based on the principle of reverse engineering, lumbar L4, L5 and intervertebral disc models were established through image segmentation, and three material attributes were assigned to the vertebral body models: (1) Gray value assignment: Gradient value was assigned by using gray value through Mimics. (2) Homogeneous and gray value mixed assignment: A single elastic modulus was given to the anterior cortical bone of the vertebral body, and gray values were used to give to the cancellous bone of the front end and the pedicle, transverse process and spinous process of the posterior end. (3) Cortical bone and cancellous bone assignment: Two elastic moduli of cortical bone and cancellous bone were used. The finite element model under the three assignment methods was loaded with an axial load of 100-500 N. The bending moments of 2, 4, 6, 8, and 10 N·m were applied to simulate the vertebral body to perform forward flexion, backward extension, left and right lateral bending and left and right rotation. RESULTS AND CONCLUSION: Vertebral body under different loading conditions had obvious differences in axial displacement and deflection angle. Root mean square error analysis showed that compared with the other two methods, data obtained by grey value assignment method were more close to the real experimental data. It did not produce obvious stress step phenomenon in material assignment junction, and could not produce obvious stress concentration phenomenon, was more in line with the mechanical properties of vertebral body. Thus, more accurate statics analysis of the spine can be carried out. [ABSTRACT FROM AUTHOR]