Predicting the flow stress behavior of Ni-42.5Ti-3Cu during hot deformation using constitutive equations

The hot deformation behavior of ternary Ni-42.5Ti-3Cu alloy was modeled. Hot compression tests were carried out at the temperatures from 800°C to 1000°C and at the strain rates of 0.001 s−1 to 1 s−1. The experimental results were then used to determine the constants for developing constitutive equations. There was an unacceptable fitting between the predicted and experimental results using Zener-Hollomon parameter in a hyperbolic sinusoidal equation form. The mismatches among the experimental and predicted results were observed almost for all tested conditions. By modifying the Zener-Hollomon parameter for the compensation of strain rate, a very good agreement was achieved between the predicted values and experimental ones. Both predicted and experimental stress-strain curves illustrate the occurrence of dynamic recrystallization. Also, in both cases, the peak and steady state stresses raised with decrease of temperature and increase of strain rate. The very good agreement between the measured and predicted results indicates the high accuracy of developed model and constitutive equations which can be used for predicting and analyzing the hot deformation behavior of Ni-42.5Ti-3Cu

Unfolding the neutron spectrum of a NE213 scintillator using artificial neural networks

Artificial neural networks technology has been applied to unfold the neutron spectra from the pulse height distribution measured with NE213 liquid scintillator. Here, both the single and multi-layer perceptron neural network models have been implemented to unfold the neutron spectrum from an Am-Be neutron source. The activation function and the connectivity of the neurons have been investigated and the results have been analyzed in terms of the network's performance. The simulation results show that the neural network that utilizes the Satlins transfer function has the best performance. In addition, omitting the bias connection of the neurons improve the performance of the network. Also, the SCINFUL code is used for generating the response functions in the training phase of the process. Finally, the results of the neural network simulation have been compared with those of the FORIST unfolding code for both Am-Be and Cf neutron sources. The results of neural network are in good agreement with FORIST code. Crow

Design and Optimization of the Thermo-Mechanical Behavior in Glass Reinforced Polyamide 6 For Automotive Application

In this work a rational approach, such as Design of Experiments, has been used to design E-glass and S2-glass reinforced polyamide 6 composites. The models, derived by the multivariate analysis of the experimental tests, allowed deriving response surfaces in which the effect of reinforce’s composi- tion, content and shape on the thermo-mechanical have been related to com- posite’s behavior during cycling loads and high temperatures. These composites find application in the developing of a sensor used in the automotive engine compartment where thermal and vibration effects must be taken in account to avoid premature failure. Thirty experiments were planned by Design of Exper- iments and analyzed through Analysis Of Variance to correlate reinforce’s properties to coefficient of thermal expansion, Young Modulus and damping over temperature/frequency variation. Statically reliable models were calculated to obtain a numerical estimation of the overall quadratic and cubic interactions among reinforce’s properties, explaining how matrix/reinforce interaction affects composite’s properties. Nevertheless, the employment of S2-glass led to restrained coefficient of thermal expansion of the composites, reinforce’s content of E-glass fibers over 30wt% is in a better agreement with the composite’s overall requirements for this tailored application, due to restrained mechanical damping

Vibration damping characteristics of short hemp fibre thermoplastic composites

In this project, free vibration testing and dynamic mechanical analysis methods were used to study the damping properties of noil hemp fibre-reinforced polypropylene composites with varying fibre contents (0 to 60 wt%) and compatibilizers (maleic anhydride-grafted polypropylene and maleic anhydride-grafted polyethylene octane) under applied frequencies of 1 to 200 Hz. The storage modulus of the composites was increased by the increase in hemp fibre content. However, the maximum damping ratio was obtained from the composite with 30 wt% noil hemp fibre. The addition of coupling agents reduced the damping capacity of all composites. However, 30 wt% noil hemp fibre-reinforced polypropylene coupled with 2.5 wt% anhydride-grafted poly ethylene octane revealed the highest damping ratio among coupled composites. Damping properties of the composites were relatively constant over the frequency range, except at frequencies which the material–instrument system began to resonate and peaks were observed in the curves