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.     

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

In this paper, a novel full-duplex overlay cognitive wireless powered communication network (FD-OCWPCN) is proposed where a full-duplex (FD) hybrid-access point (H-AP) supports the full access of all battery-free secondary users (SUs). The H-AP broadcasts wireless power to empower the nearby SUs in the downlink (DL) phase while decoding the information transmitted uplink (UL) phase by the SUs, simultaneously. To overcome the self-interference (SI) phenomenon in FD-OCWPCN, the problem of maximizing the system sum-throughput with optimal UL-DL transmission/reception time and H-AP’s transmit power allocation is considered. This problem is non-convex under perfect/imperfect SI cancelation (SIC), so we employ the active interference temperature control and the gradient projection techniques to effectively reduce it into a convex problem. Closed-form expressions for the perfect/imperfect SIC cases are also derived. To assess the performance of the FD-OCWPCN, a comparison with a half-duplex OCWPCN (HD-OCWPCN) is provided. The achievable average sum-throughput for different FD/HD-OCWPCN is compared in the context of the average and peak transmit power at the H-AP, the number of SUs, path loss exponent and fairness metric. The simulation results depict the superiority of the FD-OCWPCN over the HD-OCWPCN for the perfect SIC and the effective imperfect SIC.

     

Investigation of well test behavior in gas condensate reservoir using single-phase pseudo-pressure function

Gas condensate reservoirs present complicated thermodynamic behavior when pressure falls below the dew point pressure, due to fluid dropout and change in the fluid composition. Condensate blockage in the near wellbore region reduces the well deliverability. Mixture composition change in the reservoir makes the interpretation of well tests in gas condensate reservoirs a serious challenge. In this study, at first the capillary number effect and Non-Darcy Flow on compositional simulation of gas condensate reservoirs were investigated and then well test analysis was carried out. The main objective of this work was to examine gas condensate well test analysis using single-phase gas pseudo-pressure and radial composite model assuming capillary number effect and Non-Darcy Flow. For this purpose some fluid samples were selected and results compared. Results indicate that estimation of reservoir properties below the dew point is in good agreement with actual input, particularly for lean fluid samples.     

Enhancing the seismic performance of mid‐rise wood‐frame buildings with rigid spine columns

Wood‐frame buildings (WFBs) are the most commonly used structural systems for residential applications in North America. Past researches have shown that WFBs are susceptible to soft‐story mechanisms. In this study, a simple, efficient, and economical retrofit strategy, which utilizes continuous pinned‐supported rigid spine columns (RSCs) over the height of the building, is proposed. The retrofit aims to provide uniform deformation through the height of the building to prevent soft‐story mechanisms. This retrofit strategy was applied to a six‐story WFB located in Vancouver, British Columbia, Canada. A three‐dimensional nonlinear finite element model of the prototype building was developed using OpenSees. A comprehensive parametric study was conducted to identify the most economical RSC design. Seismic performance of the prototype building, with and without the most economical RSC design, was assessed through extensive nonlinear time history analyses. Results showed that the proposed retrofit strategy can effectively improve the seismic behavior of WFBs to prevent soft‐story mechanisms.     

Recent Developments for Prediction of Power of Aromatic and Non‐Aromatic Energetic Materials along with a Novel Computer Code for Prediction of Their Power

The explosive power or strength of an energetic material shows its capacity for doing useful work. This work reviews recent developments for prediction of power of energetic compounds. A new user‐friendly computer code is also introduced to predict the relative power of a desired energetic compound as compared to 2,4,6‐trinitrotoluene (TNT). It is based on the best available methods, which can be used for different types of energetic compounds including nitroaromatics, nitroaliphatics, nitramines, and nitrate esters. The computed relative powers are consistent with the measured data for some new materials containing complex molecular structures.