Predicting cetane number,kinematic viscosity,density and higher heating value of biodiesel from its fatty acid methyl ester composition

Biodiesel is a renewable bio-fuel derived from natural fats or vegetable oils, and it is considered as a promising alternative to substitute diesel fuels. Cetane number, viscosity, density, and higher heating value are important properties to affect the utilization of biodiesel fuels, because they are involved in the definition of fuel quality and are required as input data for predictive engine combustion models. This work presents the characterization of two biodiesel samples made from beef tallow and soybean oil through their fatty acid methyl esters (FAMEs) profile. Empirical equations were developed to estimate four physical properties of methyl esters; and an average absolute deviation (AAD) of 5.95%, 2.57%, 0.11% and 0.21% for the cetane number, kinematic viscosity, density, and higher heating value were founded. Cetane number, viscosity, and higher heating value increases because of the increase of molecular weight and these physical properties decrease as the number of double bonds increases. Unlike that of above properties, density decreases as molecular weight increases and density increases as the degree of unsaturation increases. Two general mixing rules and five biodiesel samples were used to study the influence of FAMEs over the physical properties of biodiesel. The prediction of the cetane number, kinematic viscosity, density and higher heating value of biodiesel is very close to the experimental values.     

Supercomputing and grid computing on the verification of covering arrays

The Covering Arrays (CAs) are mathematical objects with minimal coverage and maximum cardinality that are a good tool for the design of experiments. A?covering array is an N×k matrix over an alphabet v s.t. each N×k subset contains at least one time each combination from {0,1,??,v?1} ^t , given a positive integer value?t. The process of ensuring that a CA contains each of the v ^t combinations is called verification of CA. In this paper, we present an algorithm for CA verification and its implementation details in three different computation paradigms: (a)?sequential approach (SA); (b)?parallel approach (PA); and (c)?Grid approach (GA). Four different PAs were compared in their performance of verifying a matrix as a CA; the PA with the best performance was included in a different experimentation where the three paradigms, SA, PA, and GA were compared in a benchmark composed by 45 possible CA instances. The results showed the limitations of the different paradigms when solving the verification of CA problem, and points out the necessity of a Grid approach to solve the problem when the size of a CA grows.     

A multiobjective GRASP–VND algorithm to solve the waste collection problem

In this paper, the waste collection problem (WCP) of a city in the south of Spain is addressed as a multiobjective routing problem that considers three objectives. From the company's perspective, the minimization of the travel cost is desired as well as that of the total number of vehicles. Additionally, from the employee's point of view, a set of balanced routes is also sought. Four variants of a multiobjective hybrid algorithm are proposed. Specifically, a GRASP (greedy randomized adaptive search procedure) with a VND (variable neighborhood descent) is combined. The best GRASP–VND algorithm found is applied in order to solve the real‐world WCP of a city in the south of Spain.     

In-plane shear behaviour of thin low reinforced concrete panels for earthquake re-construction

Low reinforced thin concrete panels have been used for the re-construction of living buildings in the devastated zone of L’Aquila. A structural characterization of these types of panels is presented in this paper, paying particular attention to the fact that these panels are subjected mainly to shear forces. Refined compression-field theory (RCFT) has recently been proposed in order to better predict the behaviour of reinforced concrete members subjected to in-plane shear and axial stresses. This theory is based on continuum mechanics, i.e. satisfying compatibility, equilibrium and formulating the constitutive equations in terms of average (i.e. “smeared”) stresses and strains. The improvement of RCFT in comparison with the two most famous theories for reinforced concrete member subjected to shear [i.e. the modified compression-field theory (MCFT), and the rotating-angle softened-truss model (RA-STM)], deals with an embedded bar model based on the tension stiffening model in concrete. After an ad-hoc calibration procedure, the RCFT is employed in order to reproduce the envelope of the experimental load-deflection response of three full-scale thin low reinforced concrete panels subjected to cyclic loading. The predictions provided by RCFT are compared with the experimental data as well as with those provided by MCFT and RA-STM. This paper presents the necessary parameters for the design of thin low reinforced concrete panels using the RCFT. The preliminary numerical validations seem very promising. However, additional experimental data are required for calibrating and validating the parameters of the proposed RCFT theory.     

An efficient algorithm for optimal routing applied to convoy merging manoeuvres in urban environments

This paper describes an innovative routing strategy for intelligent transportation units willing to perform merging manoeuvres with a moving convoy. In particular, we consider a transportation unit located inside a city (pursuer unit), and which wishes to join a convoy that is constantly moving around the city. We first describe a solution that considers idealistic conditions, i.e., the traveling time along each street is constant. We then go on to improve our first approach to deal with the realistic random nature of the traveling times experienced by the pursuer and by the convoy leader. Our search strategy applies Dynamic Programming to achieve a meeting point that is optimal in two ways: on one hand, the optimal destination is the one closest to the current pursuer??s position; on the other hand, the optimal meeting point must minimize the time that elapses until the pursuer meets the convoy (considering that the pursuer must always arrive first). Calculating the optimal path to every possible destination is highly inefficient, error prone and time consuming. On the contrary, we propose an efficient search strategy that will achieve the meeting point and the path to it, both optimally and in a very short time. This enables the real-time application of our approach either for finding new solutions or for re-planning old ones owing to unexpected real-conditions.     

Varietal discrimination of Chilean wines by direct injection mass spectrometry analysis combined with multivariate statistics

A simple, direct injection, electrospray ionization Fourier transform mass spectrometry (ESI FT-MS) method, in combination with multivariate statistics, was used for the characterization and sorting of Chilean wines. 47 commercial red wines labelled as Cabernet Sauvignon, Carménère, Syrah, and Pinot noir, and 25 white wines of the varieties Chardonnay and Sauvignon blanc were diluted, directly infused into the mass spectrometer, and analyzed in negative ion mode. The signature ions used for statistical analyses were manually filtered out from the signals with m/z ratios over 10%. The results of principal component analysis allowed a good sorting of white wines, but not so in the case of reds. The main three principal components explained 96.82% and 85.65% of the variance for white and red wines, respectively. Instead, linear discriminant analysis, allowed the correct discrimination of 100.00% of white and 95.74% of red samples. The validation of these results using the leave-one-out cross-validation method gave lower percentages of correct classification (76.00% and 61.70% of white and red samples respectively), suggesting that some of the wine samples analyzed might have been blends of more than one variety. Consequently, ESI FT-MS direct injection analysis of wines can be used for sample discrimination, but requires a stronger mathematical model built with spectral information of pure and blended samples before improving the percentages of classification.     

ZnO@Ni foam photoelectrode modified with heteroatom doped graphitic carbon for enhanced photoelectrochemical water splitting under solar light

In this study, an electrocatalyticaly inactive ZnO@Ni foam photoelectrode was modified with heteroatom doped graphitic carbon to achieve enhanced photoelectrochemical (PEC) water splitting performance. The O, S and N doped graphitic carbon was simultaneously deposited with ZnO on Ni foam substrate under hydrothermal deposition. One dimensional ZnO nanorods with flower-like graphitic carbon on their surface were obtained on the Ni foam substrate, which was directly used as photoelectrode to derive photoelectrochemical water splitting under solar light irradiation. The pristine ZnO@NF exhibit unattractive PEC performance evidenced by the high overpotential required for the oxygen evolution reaction (OER) couple of water splitting reaction (398 mV vs. RHE). The carbon modified ZnO–C@NF photoelectrode lowers the overpotential required to 317 mV. This enhancement was attributed to the carbon modification which serves as both active site and photoelectron reservoir; facilitating the sluggish kinetics of OER couple reaction and promoting separation of photogenerated charge carriers.     

An adaptive color similarity function suitable for image segmentation and its numerical evaluation

In this article, we present an adaptive color similarity function defined in a modified hue‐saturation‐intensity color space, which can be used directly as a metric to obtain pixel‐wise segmentation of color images among other applications. The color information of every pixel is integrated as a unit by an adaptive similarity function thus avoiding color information scattering. As a direct application we present an efficient interactive, supervised color segmentation method with linear complexity respect to the number of pixels of the input image. The process has three steps: (1) Manual selection of few pixels in a sample of the color to be segmented. (2) Automatic generation of the so called color similarity image (CSI), which is a gray level image with all the gray level tonalities associated with the selected color. (3) Automatic threshold of the CSI to obtain the final segmentation. The proposed technique is direct, simple and computationally inexpensive. The evaluation of the efficiency of the color segmentation method is presented showing good performance in all cases of study. A comparative study is made between the behavior of the proposed method and two comparable segmentation techniques in color images using (1) the Euclidean metric of the a* and b* color channels rejecting L* and (2) a probabilistic approach on a* and b* in the CIE L*a*b* color space. Our testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. It was obtained from the results that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume in the CIE L*a*b* color space. We show that our solution improves the quality of the proposed color segmentation technique and its quick result is significant with respect to other solutions found in the literature. The method also gives a good performance in low chromaticity, gray level and low contrast images. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 156–172, 2017