Liquid metal corrosion of 316L,Fe<Subscript>3</Subscript>Al,and FeCrSi in molten Zn-Al baths

Corrosion tests of 316L and two intermetallic compounds Fe₃Al and FeCrSi in industrial Galvanizing (Zn-0.18Al), GALFAN (Zn-5Al), GALVALUME (Zn-55Al), and Aluminizing (Al-8Si) baths and lab-scale static baths were conducted. In on-line tests in industrial hot-dip baths, 316L steel shows better corrosion resistance than Fe₃Al in Galvanizing, GALFAN, and GALVALUME baths. The corrosion resistance of 316L and Fe₃Al is similar in Aluminizing bath. In static tests, FeCrSi shows the best corrosion resistance in pure Zn, Zn-55Al, and Al-8Si baths. The corrosion resistance of 316L is better than that of Fe₃Al. In Zn-5Al bath, 316L shows no thickness loss after the test. For the same bath composition, the corrosion rates of the alloys in industrial baths are higher than those in static baths. Bath temperature and chemical composition play important roles in corrosion and intermetallic layer formation. Increasing bath temperature accelerates the corrosion process and changes the nature of intermetallic layers. A small amount of aluminum reduces the corrosion process by reducing the activity of Zn and forming inhibition layer. However, after aluminum content reaches the critical point, the dominant corrosion process changes from Zn-Fe reaction to Al-Fe reaction, and, consequently, the corrosion process accelerates by increasing aluminum content in the bath.     

Early bankruptcy prediction using ENPC

Bankruptcy prediction has long time been an active research field in finance. One of the main approaches to this issue is dealing with it as a classification problem. Among the range of instruments available, we focus our attention on the Evolutionary Nearest Neighbor Classifier (ENPC). In this work we assess the performance of the ENPC comparing it to six alternatives. The results suggest that this algorithm might be considered a good choice.     

Fast Separation of Capsaicinoids from Peppers by Reversed Phase Ultra-Performance Liquid Chromatography: Comparation with Traditional High-Performance Liquid Chromatography Methods

A new chromatographic method for the separation of major capsaicinoids in peppers has been developed. Nordihydrocapsaicin, capsaicin, dihydrocapsaicin, homocapsaicin, and homodihydrocapsaicin have been separated by reversed-phase ultra-performance liquid chromatography. A gradient method has been developed using two solvents: 0.1% acetic acid in water and 0.1% acetic acid in methanol. The developed method allows the full separation of capsaicinoids in less than 3 min, with high reproducibility (relative standard deviation < 4.3%) and repeatability (relative standard deviation < 3.6%). Robustness regarding the total amount of methanol in the sample was determined. Comparison with previous reversed-phase high-performance liquid chromatography methods using both monolithic and conventional columns was also studied. Finally, the method was applied in the determination of major capsaicinoids in 16 hot pepper samples produced in Spain.     

Clipping algorithms for solving the nearest point problem over reduced convex hulls

The nearest point problem (NPP), i.e., finding the closest points between two disjoint convex hulls, has two classical solutions, the Gilbert-Schlesinger-Kozinec (GSK) and Mitchell-Dem’yanov-Malozemov (MDM) algorithms. When the convex hulls do intersect, NPP has to be stated in terms of reduced convex hulls (RCHs), made up of convex pattern combinations whose coefficients are bound by a μ<1 value and that are disjoint for suitable μ. The GSK and MDM methods have recently been extended to solve NPP for RCHs using the particular structure of the extreme points of a RCH. While effective, their reliance on extreme points may make them computationally costly, particularly when applied in a kernel setting. In this work we propose an alternative clipped extension of classical MDM that results in a simpler algorithm with the same classification accuracy than that of the extensions already mentioned, but also with a much faster numerical convergence.     

The triple point of pure normal-deuterium

The triple point temperature of pure normal-deuterium was determined on IPTS-68 using a calorimetric technique in an adiabatic cryostat and samples of about 0.2 mol of deuterium, 99.86% pure, permanently sealed in small metal cells. The temperature value was found to be 18.729 ± 0.002 K. Two thirds of the quoted uncertainty was due to the differences in IPTS-68 calibrations from NBS, NPL and PRM); differences in a range of 4.2 mK were observed using five calibrated thermometers. Natural para-ortho conversion rate was observed to be 7 ± 2h^?1 at 18.7 K; the rate of conversion back to normal composition for the gas at 20 MPa and ambient temperature was 3 ± 1h¹. The enthalpy of melting was 199 ± 1 Jmol^?1.     

Allylsilanes and vinylsilanes from silylcupration of carbon-carbon multiple bonds: scope and synthetic applications

Silylcupration of multiple bonds (allenes, acetylenes, dienes, and styrenes) has become one of the most efficient procedures for the synthesis of vinyl- and allylsilanes. These substrates are useful building blocks in organic synthesis since they undergo a great variety of silicon-assisted transformations. The methodology reported has been widely used in the synthesis of different natural products, as well as in the construction of carbo- and heterocycles. In this Account, we wish to illustrate our contribution to this field, as well as to highlight the contributions of others.     

Analysis of source term aspects in the experiment Phebus FPT1 with the MELCOR and CFX codes

Several aspects related to the source term in the Phebus FPT1 experiment have been analyzed with the help of MELCOR 1.8.5 and CFX 5.7 codes. Integral aspects covering circuit thermalhydraulics, fission product and structural material release, vapours and aerosol retention in the circuit and containment were studied with MELCOR, and the strong and weak points after comparison to experimental results are stated. Then, sensitivity calculations dealing with chemical speciation upon release, vertical line aerosol deposition and steam generator aerosol deposition were performed. Finally, detailed calculations concerning aerosol deposition in the steam generator tube are presented. They were obtained by means of an in-house code application, named COCOA, as well as with CFX computational fluid dynamics code, in which several models for aerosol deposition were implemented and tested, while the models themselves are discussed.     

APPLIED COMPUTATIONAL INTELLIGENCE FOR FINANCE AND ECONOMICS

This article introduces some relevant research works on computational intelligence applied to finance and economics. The objective is to offer an appropriate context and a starting point for those who are new to computational intelligence in finance and economics and to give an overview of the most recent works. A classification with five different main areas is presented. Those areas are related with different applications of the most modern computational intelligence techniques showing a new perspective for approaching finance and economics problems. Each research area is described with several works and applications. Finally, a review of the research works selected for this special issue is given.