Quantitative Microstructural Analysis of Formability Enhancement in Dual Phase Steels Subject to Electrohydraulic Forming

Under certain conditions, strain rate sensitive materials such as dual phase steels, show formability improvement under high strain rate forming which is known as hyperplasticity. In this research, two commercial dual phase steel sheets, DP500 and DP780, were formed under quasi-static conditions using the Nakazima test and under high strain rate conditions by electrohydraulic forming (EHF) into a conical die. Macro-strains, measured from electro-etched circle grids with an FMTI analyzer, showed remarkable formability improvement in EHF specimens. Micro-strains, i.e., the strains in the ferrite and the martensite, were calculated by quantitative metallography of more than 7000 ferrite grains and 10,500 martensite islands. The goal was to investigate the deformation improvement of the constituents under EHF. Around 20 and 100% deformation improvements were observed in ferrite and martensite, respectively. Furthermore, as a micro-mechanical modeling technique, correlation of the micro-strains with the macro-strains was investigated by applying the mixture rule. Results showed a reasonable correlation between the macro and micro-scale strains; however in banded microstructures, the strain in the martensite should be determined precisely for more accuracy.     

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC₁’s) scores, the MSPI would be simply attained by dividing PC₁’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC₁ is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.     

Moisture susceptibility of warm mixed-reclaimed asphalt pavement containing Sasobit and Zycotherm additives

In this research, the influence of Sasobit and Zycotherm on the properties of reclaimed asphalt pavement (RAP)-warm mix asphalt (WMA) was investigated. Moisture susceptibility was evaluated applying the resilient modulus ratio, the indirect tensile strength ratio, and the fracture energy ratio. Laboratory testing results indicated that Zycotherm mixtures had more resistance to moisture damage than Sasobit WMA and hot mix asphalt (HMA) mixtures. The stiffness of mixtures increased dramatically by increasing the amount of RAP and using Sasobit exacerbated this problem.     

Prediction of hydrate equilibrium conditions using k-nearest neighbor algorithm to CO2 capture

Gas or clathrate hydrates are an important issue when they form in the oil and gas pipelines. Since the determination of the hydrate formation temperature and pressure is very difficult experimentally for every gas system and it is impossible in terms of cost and time approximately, mathematical models can be useful tools to overcome these difficulties. In this study, k-nearest neighbor model was used to predict the equilibrium conditions of hydrate formation in absorption and separation of carbon dioxide from flue gas mixture, containing carbon dioxide and nitrogen. At the training phase, temperature and composition data of nitrogen and carbon dioxide in the flue gas mixture at equilibrium conditions and the equilibrium pressures of hydrate formation were used as input and output, respectively. The error percentage less than 0.38% indicates the high accuracy of the proposed model. In this study, 80%, 85%, and 90% of the training data are examined for three numbers of nearest. For three numbers of used nearest (k = 1, k = 2 and k = 3), the value of k = 1 leads to the lowest error; so, it is selected as the best nearest in the presented model.     

3D FEM analysis,dynamic modeling,and performance assessment of transverse flux PMSG for small‐scale gearless wind energy conversion systems

The transverse flux permanent magnet synchronous generator has a great potential for use in direct‐drive wind energy conversion systems due to its large pole numbers, high torque, and power density. This research work develops dynamic model of a single‐side transverse flux permanent magnet synchronous generator for use in a small‐scale gearless wind energy conversion system. For acquiring the parameters of the considered generator, required for dynamic modeling, 3D finite element model of the machine is developed and analyzed in both magneto‐static and transient modes. Field‐oriented control approach is employed for tracking maximum power point from the variable wind speed. The simulation results illustrate an accurate response of the system to the wind speed variation and proper performance of the developed dynamic model and control approach of the system. Copyright © 2015 John Wiley & Sons, Ltd.     

Probabilistic assessment of torsion in concrete beams externally strengthened with CFRP composites

This paper illustrates an analytical probabilistic study of concrete beams subjected to torsion that are strengthened with carbon fiber reinforced polymer (CFRP). Hii and Al-Mahaidi’s method is one of the best analytical models for evaluating the torsional capacity of CFRP strengthened reinforced concrete beams. The first-order reliability method is carried out to probabilistically assess the capacity of CFRP-strengthened beams. For this aim, the statistical characteristics of design variables and model errors have been considered, followed by the determination of the average reliability indexes of the strengthened beams. The effect of each design variable on the average reliability is also determined. The assessment shows that the Hii and Al-Mahaidi’s analytical model is unconservative. In order to correct the situation, a more relaxed set of resistance factors for use in a load and resistance factor design format are needed. These are then determined for two target reliability levels of $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5. It is found that factors of 0.9200 and 0.8225 are needed for target reliability levels, $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5, respectively. Values of 0.9 and 0.8 are suggested for use in real practice depending on the target reliability sought.     

Numerical investigation of the mechanism behind the deflagration to detonation transition in homogeneous and inhomogeneous mixtures of H2-air in an obstructed channel

The accidental release of hydrogen into enclosures can result in a flammable mixture with concentration gradients and possible deflagration-to-detonation transition (DDT). This numerical study aims to investigate the effect of obstacle spacing and mixture concentration on the DDT in a homogeneous and inhomogeneous hydrogen-air mixture. The paper focuses on the mechanisms behind the DDT in two mixtures with an average hydrogen concentration of 15% and 30%. Unlike the near-stoichiometric mixture, in the lean mixture, DDT only occurs in the inhomogeneous mixture. Depending on obstacle spacing, three different regimes of DDT were observed in the near-stoichiometric inhomogeneous mixture: i) Detonation was ignited when a strong Mach stem formed and propagated between the obstacles; ii) two explosion centers appeared when incident shock and Mach stem reflected from upper and lower obstacles, respectively; iii) Mach stem did not form but DDT occurred behind the flame front at the top of the obstacle.     

Acidic sulphate leaching of chalcopyrite concentrates in presence of pyrite

Copper concentrates with mineralogy dominated by chalcopyrite have slow leaching kinetics at atmospheric pressure in sulphate media because of the formation of passivation layer on its surface during the leaching. To enhance the leaching rate of the copper concentrate, pyrite was added to act as a catalyst. Pyrite and copper sulphide minerals then form a galvanic cell which increases both the copper leaching rate and yield. Effect of parameters such as solution redox potential, temperature, initial acid concentration, solids content, total initial iron concentration and pyrite to copper sulphide minerals mass ratio were investigated. Mineralogical analyses by XRD were performed on selected leach residues and the feed materials. A copper recovery higher than 80% in 24 h was achieved at a redox potential of 410 mV vs Ag, AgCl, a temperature of 85 °C, 15 g/L of initial acid concentration, a solid content of 7.8% (w/v), a total initial iron concentration 5 g/L and pyrite to copper sulphide minerals mass ratio 2:1. XRD patterns on leach residues showed that candidates for surface passivation, i.e. jarosite and elemental sulphur, were formed at high total initial iron concentrations.     

The S-transform using a new window to improve frequency and time resolutions

The S-transform presents arbitrary time series as localized invertible time–frequency spectra. This transformation improves the short-time Fourier transform and the wavelet transform by merging the multiresolution and frequency-dependent analysis properties of wavelet transform with the absolute phase retaining of Fourier transform. The generalized S-transform utilizes a combination of a Fourier transform kernel and a scalable-sliding window. The common S-transform applies a Gaussian window to provide appropriate time and frequency resolution and minimizes the product of these resolutions. However, the Gaussian S-transform is unable to obtain uniform time and frequency resolution for all frequency components. In this paper, a novel window based on the $t$ student distribution is proposed for the S-transform to achieve a more uniform resolution. Simulation results show that the S-transform with the proposed window provides in comparison with the Gaussian window a more uniform resolution for the entire time and frequency range. The result is suitable for applications such as spectrum sensing.     

Highly Conductive Carbon Nanotube‐Graphene Hybrid Yarn

An efficient procedure for the fabrication of highly conductive carbon nanotube/graphene hybrid yarns has been developed. To start, arrays of vertically aligned multi‐walled carbon nanotubes (MWNT) are converted into indefinitely long MWNT sheets by drawing. Graphene flakes are then deposited onto the MWNT sheets by electrospinning to form a composite structure that is transformed into yarn filaments by twisting. The process is scalable for yarn fabrication on an industrial scale. Prepared materials are characterized by electron microscopy, electrical, mechanical, and electrochemical measurements. It is found that the electrical conductivity of the composite MWNT‐graphene yarns is over 900 S/cm. This value is 400% and 1250% higher than electrical conductivity of pristine MWNT yarns or graphene paper, respectively. The increase in conductivity is asssociated with the increase of the density of states near the Fermi level by a factor of 100 and a decrease in the hopping distance by an order of magnitude induced by grapene flakes. It is found also that the MWNT‐graphene yarn has a strong electrochemical response with specific capacitance in excess of 111 Fg^?1. This value is 425% higher than the capacitance of pristine MWNT yarn. Such substantial improvements of key properties of the hybrid material can be associated with the synergy of MWNT and graphene layers in the yarn structure. Prepared hybrid yarns can benefit such applications as high‐performance supercapacitors, batteries, high current capable cables, and artificial muscles.