Influence of Silicon Morphology and Mechanical Properties of Piston Alloys

In this paper, the influence of silicon particle morphology on mechanical properties of two piston alloys has been reported. Alloys having nominal composition Al-12%Si-1%Ni-0.8%Cu-0.6%Mg (LM13) and Al-17%Si-1%Ni-0.8%Cu-0.6%Mg (LM28) were prepared by melting and casting. The morphology of silicon crystals was changed using additives during the melt treatment and subsequently by heat treatment. Mechanical properties such as hardness, ductility, and tensile strength of experimental alloys were tested. Test results showed that the melt treatment and heat treatment of both the alloys increased the tensile strength, hardness, and ductility. However, the influence of melt treatment on mechanical properties was not as significant as that of heat treatment. Tensile strength and ductility of LM13 was found to be higher than the LM28 alloy under similar conditions. Hardness of LM28 was higher than the LM13 alloy. Optical and SEM studies showed a change in eutectic silicon morphology on melt treatment of LM13. However, change in morphology of primary silicon particles was not significant as for LM28. Heat treatment of both alloys caused spheroidization and better distribution of eutectic silicon crystals. Sharp-edged primary silicon particles were rounded off after the heat treatment of LM28. Scanning electron microscopy (SEM) of tensile fractured surfaces was carried out to study the influence of microstructure on fracture mode. Heat treatment of both alloys promotes dimple fracture. However, as-cast and melt-treated alloys show predominantly cleavage fracture.     

Morphology,Mineralogy and Mixing of Individual Atmospheric Particles Over Kanpur (IGP): Relevance of Homogeneous Equivalent Sphere Approximation in Radiative Models

Estimation of the direct radiative forcing (DRF) by atmospheric particles is uncertain to a large extent owing to uncertainties in their morphology (shape and size), mixing states, and chemical composition. A region-specific database of the aforementioned physico-chemical properties (at individual particle level) is necessary to improve numerically-estimated optical and radiative properties. Till date, there is no detailed observation of the above mentioned properties over Kanpur in the Indo-Gangetic Plain (IGP). To fill this gap, an experiment was carried out at Kanpur (IITK; 26.52°N, 80.23°E, 142 m msl), India from April to July, 2011. Particle types broadly classified as (a) Cu-rich particles mixed with carbon and sulphur (b) dust and clays mixed with carbonaceous species (c) Fe-rich particles mixed with carbon and sulfur and (d) calcite (CaCO₃) particles aged with nitrate, were observed. The frequency distributions of aspect ratio (AR; indicator of extent of particle non-sphericity) of total 708 particles from April to June reveal that particles with aspect ratio range >1.2 to ≤1.4 were abundant throughout the experiment except during June when it was found to shift to high AR range, >1.4 to ≤1.6 (followed with another peak of AR i.e. >2 to ≤2.4) due to dust storm conditions enhancing the occurrence of more non-spherical particles over the sampling site. The spherical particles (and close to spherical shape; AR range, 1.0 to ≤1.2) were found to be <20% throughout the experiment with a minimum (11.5%) during June. Consideration of Homogeneous Equivalent Sphere Approximation (HESA) in the optical/radiative model over the study region is found to be irrelevant during the campaign.     

Comparative study of artificial neural network for classification of hot and cold recombination regions in Saccharomyces cerevisiae

At the chromosomal level of evolution, recombination is a major factor for genetic variations. However, recombination does not occur with equal frequency at various regions of genome. The recombination has the tendency to occur at specific region with higher frequency and with low frequency at other regions, and former regions are named as hot recombination regions whereas later are called cold regions for recombination. In this paper, we have developed supervised machine learning-based models using artificial neural network, support vector machine and Naïve Bayes for efficient and effective classification of such hot and cold recombination regions based on the nucleotide composition of sequences. All models were validated and tested using tenfold cross-validation. Furthermore, neural network model was validated using leave one out and random sampling techniques in addition to tenfold cross-validation. Moreover, models were evaluated using receiver-operating curve. Our results indicate that artificial neural network achieves the best result.

     

Speed–density functional relationship for heterogeneous traffic data: a statistical and theoretical investigation

This study is an attempt to establish a suitable speed–density functional relationship for heterogeneous traffic on urban arterials. The model must reproduce the traffic behaviour on traffic stream and satisfy all static and dynamic properties of speed–flow–density relationships. As a first attempt for Indian traffic condition, two behavioural parameters, namely the kinematic wave speed at jam (C_j) and a proposed saturation flow (λ), are estimated using empirical observations. The parameter C_j is estimated by developing a relationship between driver reaction time and vehicle position in the queue at the signalised intersection. Functional parameters are estimated using Levenberg–Marquardt algorithm implemented in the R statistical software. Numerical measures such as root mean squared error, average relative error and cumulative residual plots are used for assessing models fitness. We set out several static and dynamic properties of the flow–speed–density relationships to evaluate the models, and these properties equally hold good for both homogenous and heterogeneous traffic states. From the numerical analysis, it is found that very few models replicate empirical speed–density data traffic behaviour. However, none of the existing functional forms satisfy all the properties. To overcome the shortcomings, we proposed two new speed–density functional forms. The uniqueness of these models is that they satisfy both numerical accuracy and the properties of fundamental diagram. These new forms would certainly improve the modelling accuracy, especially in dynamic traffic studies when coupling with dynamic speed equations.

     

Impulse Pressure Assisted Diffusion Bonding of Low Carbon Steel Using Silver Interlayer

In the present study, impulse pressure assisted diffusion bonding of low carbon steel was carried out using silver interlayer. To study the influence of input process parameters namely bonding temperature (T), maximum pulse pressure (P), and number of pulses (N), experiments of diffusion bonding were conducted according to the Taguchi L9 orthogonal array. To reveal the typical bond interface characteristics, selected samples were examined by scanning electron microscopy (FESEM) equipped with energy dispersive spectroscopy (EDS). The EDS analysis revealed a diffusion affected zone at the interface due to the diffusion of silver and iron across the interface. Lap joints were developed to measure the shear strength of the diffusion bonds. The optimum level of bonding temperature, maximum pulse pressure and number of pulses (875 °C, 10 MPa and 10 pulses) were identified. The ANOVA results indicated that bonding temperature had the highest statistical effect of 66.37% on shear strength followed by number of pulses and maximum pulse pressure. The fracture surface of the lap joints was also examined by FESEM and X-ray diffraction analysis.     

Service delivery through mobile-government (mGov): Driving factors and cultural impacts

The mobile-Government (mGov) service system is conducted through an open network, and it is virtual. This service mode and pattern change inevitably necessitates a behavioral change in citizen attitudes and intentions. Nevertheless, this new pattern of service delivery through mGov has hardly been systematically investigated by any researchers. The objective of this current research is twofold. First, we attempt to reveal the sources of beliefs for developing intention toward the mGov (ITM) system. Then, as the second objective, we investigate cultural influence as the reason for a difference in consumer attitudes and intentions toward mGov. In this regard, the empirical study was conducted in Bangladesh and the USA, which have potential differences in the cultural traits listed by Hofstede. From our statistical analysis, we have identified the sources of beliefs for both Bangladeshi and USA consumers. We observed clear differences in sources of beliefs and their influence on attitudes leading to intention, which demonstrates support for our second objective which was designed to verify the cultural impacts on belief-attitude relations. We understand that these different sources of beliefs influence cognitive, affective, and connative attitudes toward mGov in different ways.     

An improved tri-reforming based methanol production process for enhanced CO2 valorization

The consistent rise of CO₂ concentration in the atmosphere is known to be significantly detrimental to the environment. Thus, mitigating CO₂ has become an urgent necessity. Current methods involving CO₂ mitigation can be broadly divided into two major categories which involve (i) CO₂ capture and sequestration (CCS) and (ii) CO₂ capture and valorization. Since, production of fuels/chemicals is an added feature along with mitigation in CO₂ valorization based methods, they could be economically favorable. An energy intensive CO₂ capture step is a common drawback of most CO₂ valorization methods that aim to mitigate CO₂ from major CO₂ emission sources (such as industrial flue gases). In this paper we employ and analyze a relatively new process called tri-reforming [1,2] which was developed to directly convert power plant based flue gases to synthesis gas, while avoiding the capture step. This paper is presented as an improvement over a tri-reforming coupled methanol production process as developed by Zhang et al. [3]. The process in Zhang et al. [3] involves utilizing tri-reforming process using flue gas and methane to produce synthesis gas which is then converted to methanol in the next step. The main contributions of this paper to the tri-reforming coupled methanol production process are: (i) proposition of a high pressure tri-reforming step to limit capital costs of the process (ii) establishment of steam input coupled with water separation step as a process improvement whose impact is shown to further amplify at higher tri-reformer pressures. The paper evaluates the process in terms of the profit generating and CO₂ valorization potential of the process as reflected by two parameters, gross margin (GM) and NPCV (net percentage of CO₂ valorized) respectively. In the proposed approach, higher pressures were utilized in the tri-reforming process to ensure economic feasibility of the process by limiting the reactor volume. The process improvements for the flowsheet containing the steam input combined with water separation (SWS) step over the one without these steps (termed as WSWS) are demonstrated in terms of an increase in GM/NPCV values at various pressures. The results indicate substantial improvements in GM and NPCV values (especially at higher tri-reformer pressures) ranging from 24.30 to 84.96% and 28.80–78.44% respectively in SWS cases over WSWS cases at various pressures. The simulations have been carried out in Aspen Plus V8.4 and are optimized using sensitivity analysis.     

Effect of relative humidity and light conditions on the oxidative stability of sunflower oil blends stabilised with synthetic and natural antioxidants

The effect of relative humidity (RH) and light conditions on the oxidative stability of sunflower oil (SO) stabilised with oleoresin rosemary + ascorbyl palmitate (SOR), sage + ascorbyl palmitate (SOS) and tertiary butyl hydroquinone (SOT) was investigated. The SO without additive (SOC) served as positive control. Oil samples were subjected to 3 RH (29%, 52% and 75%) and two light conditions (dark, D and fluorescent light (600 lx), L) at 60 °C for 7 days. The oxidative stability was monitored by peroxide value (PV), conjugated diene value (CDV), free fatty acids (FFAs) and Rancimat induction period (IP). A direct relationship was noted between RH and increase in PV, CDV and FFA levels irrespective of light conditions. The detrimental effect of light on the oxidative stability was prominently noted at higher RH (75%) which followed an order: SOC > SOT > SOR > SOS. The samples stored under lower RH (29% and 52%), and dark conditions were better stabilised than light‐exposed counterparts.     

Performance evaluation of different machine learning techniques for prediction of heart disease

Neural Computing and Applications - Heart diseases are of notable public health disquiet worldwide. Heart patients are growing speedily owing to deficient health awareness and bad consumption...     

Fatigue performance of friction stir welded Al2024 alloy in a different corrosive environment

The study examines the corrosion fatigue behavior of friction stir welded Al2024 alloy in the corrosive medium. The fatigue tests are conducted at a stress ratio of -1 in the different corrosive medium. The decrease in the fatigue life of welded joints in the corrosive environment is attributed to an increase in the crack initiation susceptibility in the presence of corrosive media. The fractured surfaces are investigated using the scanning electron microscopy (SEM). The formation of the corrosive compounds was studied using x-ray diffractometry.