The Effect of Cold Rolling on Microstructure and Mechanical Properties of a New Cr–Mn Austenitic Stainless Steel in Comparison with AISI 316 Stainless Steel

In the present study the effect of room temperature rolling on microstructure and mechanical properties of a new Cr–Mn austenitic stainless steel (containing 12 %Cr, 23 %Mn and 0.13 %C) and AISI 316 steel was investigated. The specimens of these steels were cold rolled at various thickness reductions of 0, 12, 25, 37 and 50 %. Microstructural investigations were carried out using optical microscopy, magnetic field test and X-ray diffraction technique. Hardness and tensile test methods were also done to evaluate the mechanical properties. Results showed that some of austenite phase transformed to martensite during cold rolling in the 316 steel, while there was no strain induced transformation in the Cr–Mn steel. It was also found that the newly developed steel had higher strength and higher specific strength than those of the 316 steel, while its ductility was the same as that of the 316.     

Recovery prediction of copper oxide ore column leaching by hybrid neural genetic algorithm

The artificial neural network (ANN) and hybrid of artificial neural network and genetic algorithm (GANN) were applied to predict the optimized conditions of column leaching of copper oxide ore with relations of input and output data. The leaching experiments were performed in three columns with the heights of 2, 4 and 6 m and in particle size of <25.4 and <50.8 mm. The effects of different operating parameters such as column height, particle size, acid flow rate and leaching time were studied to optimize the conditions to achieve the maximum recovery of copper using column leaching in pilot scale. It was found that the recovery increased with increasing the acid flow rate and leaching time and decreasing particle size and column height. The efficiency of GANN and ANN algorithms was compared with each other. The results showed that GANN is more efficient than ANN in predicting copper recovery. The proposed model can be used to predict the Cu recovery with a reasonable error.     

Electrochemical Behavior Assessment of Micro- and Nano-Grained Commercial Pure Titanium in H<Subscript>2</Subscript>SO<Subscript>4</Subscript> Solutions

In this study, the electrochemical behavior of commercial pure titanium with both coarse-grained (annealed sample with the average grain size of about 45 µm) and nano-grained microstructure was compared by potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and Mott-Schottky analysis. Nano-grained Ti, which typically has a grain size of about 90 nm, is successfully made by six-cycle accumulative roll-bonding process at room temperature. Potentiodynamic polarization plots and impedance measurements revealed that as a result of grain refinement, the passive behavior of the nano-grained sample was improved compared to that of annealed pure Ti in H₂SO₄ solutions. Mott-Schottky analysis indicated that the passive films behaved as n-type semiconductors in H₂SO₄ solutions and grain refinement did not change the semiconductor type of passive films. Also, Mott-Schottky analysis showed that the donor densities decreased as the grain size of the samples reduced. Finally, all electrochemical tests showed that the electrochemical behavior of the nano-grained sample was improved compared to that of annealed pure Ti, mainly due to the formation of thicker and less defective oxide film.     

The effects of heat-shock pretreatment conditions on dark hydrogen fermentation from glucose

The effects of heat-shock pretreatment conditions on the efficiency of dark hydrogen fermentation from glucose were investigated. Anaerobic sludge was pretreated at different temperatures of 70°C, 80°C, and 90°C for different time durations including 7.5, 15, 22.5, 30, 37.5, and 45 min. All pretreatments suppressed the methanogens and no detectable methane was produced after pretreatments. Pretreatments at 90°C led to the higher hydrogen contents than 70°C and 80°C. The pretreatment at 90°C for 37.5 min led to the highest biogas yield, hydrogen yield, and hydrogen production rate of 4.31?mol/mol-glucose, 3.15?mol/mol-glucose, and 70.2?mL/h.g-VS, respectively.     

Developing a simple-to-use predictive model for prediction of hydrate formation temperature

Hydrate formation may be a common occurrence during oil and gas drilling and production operation when temperature of these solid crystalline compounds that formed in the presence of free water decreases at elevated pressure. Also, they have often been found responsible for operating difficulties at wellheads, pipelines and other processing equipment. Nowadays, because of the importance of predicting hydrate formation condition, different accurate methods have been used. Besides the experiential correlations that are common for predicting, the developments in the field of modelling led to the use of different methods in a thermodynamic way. In fact, because of the risk of experimental uncertainties and to remove the need for intricate analytic equations and empirical correlations, the computational intelligence model, which result in the lowest error and based on experimental data, is strongly proposed, in attempts to solve complex industrial problems. In this article, in order to predict gas hydrate formation condition, two smart techniques are established based on feed-forward neural network (artificial neural network (ANN)) which is optimised by imperialist competitive algorithm (ICA). The ICA-ANN model is conducted utilising the empirical data released in the literature and finally the performance of ICA-ANN model is compared with the conventional ANN model. Furthermore, they have been compared with an accurate thermodynamic model at different operating conditions. The outcomes, contrary to expectations, establish that the ICA-ANN model has poor performance when compared with the ANN.     

Nonmydriatic fluorescence-based quantitative imaging of human macular pigment distributions

We have developed a CCD-camera-based nonmydriatic instrument that detects fluorescence from retinal lipofuscin chromophores ("autofluorescence") as a means to indirectly quantify and spatially image the distribution of macular pigment (MP). The lipofuscin fluorescence intensity is reduced at all retinal locations containing MP, since MP has a competing absorption in the blue-green wavelength region. Projecting a large diameter, 488 nm excitation spot onto the retina, centered on the fovea, but extending into the macular periphery, and comparing lipofuscin fluorescence intensities outside and inside the foveal area, it is possible to spatially map out the distribution of MP. Spectrally selective detection of the lipofuscin fluorescence reveals an important wavelength dependence of the obtainable image contrast and deduced MP optical density levels, showing that it is important to block out interfering fluorescence contributions in the detection setup originating from ocular media such as the lens. Measuring 70 healthy human volunteer subjects with no ocular pathologies, we find widely varying spatial extent of MP, distinctly differing distribution patterns of MP, and strongly differing absolute MP levels among individuals. Our population study suggests that MP imaging based on lipofuscin fluorescence is useful as a relatively simple, objective, and quantitative noninvasive optical technique suitable to rapidly screen MP levels and distributions in healthy humans with undilated pupils.     

An approach to design a high power piezoelectric ultrasonic transducer

Application of ultrasonic waves has been considerably progressed during the last decade and piezoelectric ceramics have had a common use as the driving source of such waves. However, there is not enough documented information on design and technology of manufacturing a high power ultrasonic transducer. In this paper, an attempt has been made to analyze the stress produced along the oscillating PZT employed ultrasonic head by applying the principles of acoustic wave propagation. Then, based on such analysis, general principles of PZT transducer design, excited by a DC-biased alternating electrical source, has been derived and finally a typical such transducer has been designed, manufactured and tested. By employing finite element modal analysis, the resonance frequency of the transducer was determined and compared with the experimental results. It was concluded that, the constitutive piezoelectric equations referred to in most sources and books are not valid for analyzing the acoustical dynamic stress in ultrasonic transducers. Instead, the analysis should be done with considering the dynamic behavior (elastic, damping and Inertia factors) of the problem.

Hydrogen generation using activated aluminum/water reaction

The effective parameters for the Al-water reaction are studied. Salts such as sodium chloride (NaCl), potassium chloride (KCl) and barium chloride (BaCl₂) were added to Al particles and the mixture were alloyed via high-energy ball milling. It was observed that the reaction of Al/water is evolved and the reaction induction time declined significantly by the application of BaCl₂ as new modifier in comparison with NaCl and KCl. The X-ray diffraction patterns revealed that the other valuable reaction byproduct is AlOOH, which can be calcinated to gamma or alpha alumina. Microstructure of alloys were studied via FESEM and it was observed that as the time of ball milling increased the size of particles decreased. Increasing of the salt to Al powder ratio lead to increasing of hydrogen yield as well as hydrogen production rate. Effect of NaOH alkaline solution was also investigated and according to the results, solutions with higher concentration of NaOH generate higher amount of hydrogen.