A.a. Gharehaghaji, M. Palhang, and M. Shanbeh,
Volume 24, Issue 2 (1-2006)
Abstract
Artificial Neural Networks are information processing systems. Over the past several years, these algorithms have received much attention for their applications in pattern completing, pattern matching and classification and also for their use as a tool in various areas of problem solving. In this work, an Artificial Neural Network model is presented for predicting the tensile
properties of cotton-covered nylon core yarns. Multilayer Feedforward network with Back Propagation learning algorithm was used to
study the relationship and mapping among the process parameters, i.e. count of sheath part, count of core part, applying pretension to the core part, inserted twist to the core spun-yarn as well as tensile properties, i.e. breaking strength and breaking elongation. The results show that ANN is an effective method for the prediction of the tensile properties of these yarns. This is due to the fact that in each case, standard deviation of prediction error for test and train data was less than that obtained from the expreiments.
A. Panahi Moghadam, M. Seifollahi, S. M. Abbasi, S. M. Ghazi Mirsaeed,
Volume 37, Issue 2 (9-2018)
Abstract
This paper was concerned with the effect of Mg on the temperature mechanical behavior and evaluation of the microstructure. The results showed that with increasing Mg from 0 to 47 ppm, the grain size was reduced from 64 to 38 µm and the carbides volume fraction was raised from 2.2 to 4.6 vot%. Mg changed the morphology of the carbide from a coarse and continuous one to a separate one. Mg with the mechanisms of grain boundary and matrix/carbide boundary led to changing the carbide composition and also, the mechanical properties. Mg increment from 0 to 47 ppm caused the enhancement of yield strength and rupture life from 309 to 345 MPa and from 16h to 30h, respectively. Grain size and the amount of carbide were the main factors contributing to the rupture of life properties in this study. The increment of the carbide volume fraction was the main mechanism of rupture life enhancement.
H. Saki, M. Morakabati, R. Mahdavi,
Volume 40, Issue 3 (11-2021)
Abstract
Metastable beta titanium alloys have the ability to achieve different microstructures as a result of various heat treatment cycles. The aim of the present study was to create a combination of fine spherical and needle-shaped alpha phase in a metastable beta Titanium alloy (Ti-3Al-8Mo-7V-3Cr) using two-phase solution annealing and aging to improve tensile properties. In this regard, one strip of the alloy was solution annealed in the two-phase region (α+β) at 750°C. Then, some of the solution treated specimens were aged in one step and the others in two steps. The microstructural observation and phase analysis were studied by scanning electron microscope (SEM) and X-ray diffraction (XRD), respectively followed by investigating tensile properties using tensile test. The results exhibited that the microstructure of the alloy after annealing in the two-phase region (α+β) consisted of a spherical primary alpha phase of 1 μm in the beta matrix. One-step aging at 600°C resulted in a microstructure without secondary alpha layers. This heat treatment cycle resulted a yield strength of 980 MPa and fracture strain of 13.9%. Two-step aging at 300°C and 600°C led to formation of the secondary alpha layers with 0.1 μm thickness and increased the yield strength and fracture strain to 1007 MPa and 15.8%, respectively.
