Deformation behaviors of four-layered U-shaped metallic bellows in hydroforming

Because of the complex constraint effects among layers in multi-layered metallic bellows hydroforming,the stress concentration and defects such as wrinkling and fracture may easily occur.It is a key to reveal the deformation behaviors in order to obtain a sound product.Based on the ABAQUS platform,a 3 D-FE model of the four-layered U-shaped metallic bellow hydroforming process is established and validated by experiment.The stress and strain distributions,wall thickness variations and bellow profiles of each layer in the whole process,including bulging,folding and springback stages,are studied.Then deformation behaviors of bellows under different forming conditions are discussed.It is found that the wall thinning degrees of different layer vary after hydroforming,and is the largest for the inner layer and smallest for the outer layer.At folding stage,the wall thinning degree of the crown point increases lineally,and the difference among layers increases as the process going.The displacements of the crown point decrease from the inner layer to the outer layer.After springback,the U-shaped cross section changes to a tongue shape,the change of convolution pitch is much larger than the change of convolution height,and the springback values of the inner layer are smaller than the outer layer.An increase in the internal pressure and die spacing cause the maximum wall thinning degree and springback increase.With changing of process parameters,bellows with deep convolution are easily encountered wall thinning during hydroforming and convolution distortion after springback.This research is helpful for precision forming of multi-layered bellows.

The development of a knowledge base in an expert system based on the four-layer perceptron neural network

Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differential function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.

Analytics of an Imperfect Four-Layer Production Inventory Model Under Two-Level Credit Period Using Branch-and-Bound Technique

This paper explains an integrated production inventory supply chain model,which consists of a supplier,a manufacturer and a retailer under two-level credit period.One is manufacturer’s credit period offered by the supplier,and other is retailer’s credit period offered by the manufacturer.Here,the manufacturer replenishes raw materials from the supplier and produces non-deteriorating products in some cycles of equal length.It is noted that here four inventory structures have been considered to show the flow of the materials as either raw materials or finished products from supplier to retailer via manufacturer.Also in this model,manufacturer’s imperfect production has been considered.Here imperfect items are not repairable.The retailer receives good finished products from the manufacturer and sells these to his/her customers during some cycles of equal length in total time horizon.Our main objective is to find the optimal number of production and business cycles of the manufacturer such that the integrated system can get the maximum profit.The above discussed model is elaborated with the help of a numerical example,and a sensitivity analysis is done with respect to some parameters used in this model.

Analytical Study of Planar Waveguide Sensor With a Metamaterial Guiding Layer

Sensitivities of three-layer and four-layer planar waveguide sensors having metamaterial as guiding layer are analyzed for p-polarization of incident light and compared with existing results. Proposed sensors show improved cover layer sensitivity for each case of the cover layer refractive index. Also, proposed sensors demonstrate improved adlayer sensitivity for different values of adlayer thickness and adlayer refractive indices. It is observed that metamaterial has increased the evanescent field due to the unconventional nature of it, by which values of cover layer sensitivity as well as adlayer sensitivity are enhanced.