Wettability Enhancement of SiCp in Cast A356/SiCp Composite Using Semisolid Process

The effects of SiCp treatment and magnesium addition on microstructural and mechanical properties of Al356/20 wt% SiCp semisolid composites were investigated. The results showed that cleaning and oxidizing of SiCp and addition of 1 wt% Mg resulted in improving wettability, incorporation, and uniform distribution of SiCp in A356 matrix. Consequently, the ultimate tensile strength (UTS) value increased by 19% and 32% when the SiC was treated and also when Mg was added, respectively, compared to as-received SiCp. In addition, hardness value increased from 69.7 HV in as-received SiCp to 94.8 HV after SiCp treatment and addition of Mg.     

Electricity market price volatility: The case of Ontario

Price volatility analysis has been reported in the literature for most competitive electricity markets around the world. However, no studies have been published yet that quantify price volatility in the Ontario electricity market, which is the focus of the present paper. In this paper, a comparative volatility analysis is conducted for the Ontario market and its neighboring electricity markets. Volatility indices are developed based on historical volatility and price velocity concepts, previously applied to other electricity market prices, and employed in the present work. The analysis is carried out in two scenarios: in the first scenario, the volatility indices are determined for the entire price time series. In the second scenario, the price time series are broken up into 24 time series for each of the 24 h and volatility indices are calculated for each specific hour separately. The volatility indices are also applied to the locational marginal prices of several pricing points in the New England, New York, and PJM electricity markets. The outcomes reveal that price volatility is significantly higher in Ontario than the three studied neighboring electricity markets. Furthermore, comparison of the results of this study with similar findings previously published for 15 other electricity markets demonstrates that the Ontario electricity market is one of the most volatile electricity markets world-wide. This high volatility is argued to be associated with the fact that Ontario is a single-settlement, real-time market.     

Roles of Li+ and Zr4+ cations in the catalytic performances of Co(1-x)M(x)Cr(2)O(4) (M = Li, Zr; x = 0-0.2) for methane combustion

Co(1-x)M(x)Cr(2)O(4) (M = Li, Zr; x = 0-0.2) catalysts were prepared via the citric acid method and investigated for catalytic combustion of methane. Substitution at tetrahedral (A) sites with monovalent (Li) or tetravalent (Zr) metal ions led to a decrease or increase of the catalytic activity, respectively. The Co(0.95)Zr(0.05)Cr(2)O(4) catalyst proved to be the most active and its catalytic activity reached 90% of methane conversion at 448 °C, which dropped by 66 °C compared with that of the undoped CoCr(2)O(4) catalyst. XRD and Raman results indicated that lithium or zirconium substitution could modify the spinel structure and electronic properties. For lithium-doped catalysts, oxygen deficiency and a strong surface enrichment in lithium and chromium were detected. Zirconium substitution enhanced the reducibility of zirconium-doped catalysts and decreased the strength constant of both the Co-O band and the Cr-O band, which may contribute to the catalytic activity toward methane combustion. In addition, the prevalent catalytic combustion activity of the zirconium-substituted catalysts could be explained by their higher concentration of suprafacial, weakly chemisorbed oxygen.     

Numerical simulation of density-driven natural convection in porous media with application for CO2 injection projects

In this paper we investigate the mass transfer of CO₂ injected into a homogenous (sub)-surface porous formation saturated with a liquid. In almost all cases of practical interest CO₂ is present on top of the liquid. Therefore, we perform our analysis to a porous medium that is impermeable from sides and that is exposed to CO₂ at the top. For this configuration density-driven natural convection enhances the mass transfer rate of CO₂ into the initially stagnant liquid. The analysis is done numerically using mass and momentum conservation laws and diffusion of CO₂ into the liquid. The effects of aspect ratio and the Rayleigh number, which is dependent on the characteristics of the porous medium and fluid properties, are studied. This configuration leads to an unstable flow process. Numerical computations do not show natural convection effects for homogeneous initial conditions. Therefore a sinusoidal perturbation is added for the initial top boundary condition. It is found that the mass transfer increases and concentration front moves faster with increasing Rayleigh number. The results of this paper have implications in enhanced oil recovery and CO₂ sequestration in aquifers.     

Toward a better understanding of multifunctional cement-based materials: The impact of graphite nanoplatelets (GNPs)

The impact of graphite nanoplatelets (GNPs) on the physical and mechanical properties of cementitious nanocomposites was investigated. A market-available premixed mortar was modified with 0.01% by weight of cement of commercial GNPs characterized by two distinctively different aspect ratios.The rheological behavior of the GNP-modified fresh admixtures was thoroughly evaluated. Hardened cementitious nanocomposites were investigated in terms of density, microstructure (Scanning Electron Microscopy, SEM and micro–Computed Tomography, μ-CT), mechanical properties (three-point bending and compression tests), and physical properties (electrochemical impedance spectroscopy, EIS and thermal conductivity measurements). At 28 days, all GNP-modified mortars showed about 12% increased density. Mortars reinforced with high aspect ratio GNPs exhibited the highest compressive and flexural strength: about 14% and 4% improvements compared to control sample, respectively. Conversely, low aspect ratio GNPs led to cementitious nanocomposites characterized by 36% decreased electrical resistivity combined with 60% increased thermal conductivity with respect to the control sample.     

Bitumen-water interfacial tension modeling by using subtractive clustering method

Calculation of interfacial tension during bitumen production is a crucial issue in heavy crude oil history. Upon variation in pressure, temperature and phases composition, interfacial tension between bitumen and water change. In this work a sophisticated method called subtractive clustering was utilized to predict dynamic interfacial tension between bitumen and water. The subtractive clustering method is composed of optimized fuzzy logic algorithm. A data bank which is collected from open-source literature, is used to create a reliable model. Then the prediction accuracy of the measured dynamic interfacial tension using subtractive clustering have been examined. Results state that the comparison of measured interfacial tension and predicted interfacial tension indicate acceptable accuracy of proposed model. Also more than 90 percent of data points have less than 3 percent absolute error.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Multilayer assembly of ionic starches on old corrugated container recycled cellulosic fibers

In this study, old corrugated container recycled fibers were treated with polyelectrolyte multilayers consisting of biopolymer cationic starch with two degrees of substitution (DS) each in combination with one anionic starch. Pulp zeta potential, paper strength and the thin layer ellipsometry technique were applied to examine the influence of cationic starch DS on the formation of polyelectrolyte multilayers. The results indicated a significant interaction between the DS of cationic starch and the number of ionic starch layers formed. When low‐DS cationic starch was used, the pulp zeta potential and the paper strength increased significantly in assembling the first cationic layer. However, in depositing high‐DS cationic starch a greater zeta potential and a stronger influence on the paper strength were observed with a larger number of starch layers. This was confirmed by thin layer ellipsometry when a greater thickness of multilayers was achieved by employing high‐DS cationic starch to form a higher number of layers. © 2017 Society of Chemical Industry     

Observer‐based adaptive optimal output containment control problem of linear heterogeneous Multiagent systems with relative output measurements

This paper develops a relative output‐feedback–based solution to the containment control of linear heterogeneous multiagent systems. A distributed optimal control protocol is presented for the followers to not only assure that their outputs fall into the convex hull of the leaders' output but also optimizes their transient performance. The proposed optimal solution is composed of a feedback part, depending of the followers' state, and a feed‐forward part, depending on the convex hull of the leaders' state. To comply with most real‐world applications, the feedback and feed‐forward states are assumed to be unavailable and are estimated using two distributed observers. That is, a distributed observer is designed to measure each agent's states using only its relative output measurements and the information that it receives by its neighbors. Another adaptive distributed observer is designed, which uses exchange of information between followers over a communication network to estimate the convex hull of the leaders' state. The proposed observer relaxes the restrictive requirement of having access to the complete knowledge of the leaders' dynamics by all the followers. An off‐policy reinforcement learning algorithm on an actor‐critic structure is next developed to solve the optimal containment control problem online, using relative output measurements and without requiring the leaders' dynamics. Finally, the theoretical results are verified by numerical simulations.