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.     

Effects of passive vibration absorbers on the mechanisms having clearance joints

Multibody System Dynamics - In the current study, the dynamic behavior of two planar mechanisms with revolute joints, in the presence of clearances is investigated. Subsequently, a control scheme...     

\begin{document}$H_\infty$\end{document} Consensus Control of Discrete-Time Multi-Agent Systems Under Network Imperfections and External Disturbance

This paper presents a distributed control protocol for consensus control of multi-agent systems (MASs) under external disturbances and network imperfections, including communication delay and random packet dropout. To comply with the discrete nature of networked systems, in contrast to most of the existing work for MASs under network imperfections, the agents are modeled by discrete-time dynamics. The communication network is considered to be undirected, its delay is considered to be time-varying but bounded, and its packet dropout is modeled by a Bernoulli distributed white sequence. Sufficient conditions in terms of linear matrix inequalities (LMIs) for asymptotic mean-square consensus stability are derived under network imperfections without considering external disturbances. A desired disturbance attenuation level in the presence of both external disturbances and network imperfections is also provided. A simulation example is given to verify the effectiveness of the proposed approach in coping with network imperfection and disturbances.      

Determination of partial resistance factors for unreinforced masonry shear walls

Partial safety factors for resistance applied in the design equation of semi‐probabilistic formats can be obtained from the evaluation of a test database. These partial safety factors are influenced by two factors, the material uncertainty and the model uncertainty. This topic is covered in a former publication [1]. It includes the determination of a partial factor for the model uncertainty of unreinforced masonry shear walls. In this study the authors examine the next step, and calculate the partial factor of resistance applying the same method, as recommended i n EN 1990 – Annex D. In addition to the Coefficient of Variation (COV) for the model uncertainty, the calculation of the resistance partial factor considers deviations in geometry, as well as loading and material properties. The influence of the material uncertainty on structural performance is considered in the calculation by means of a weighted average of all COV values for various types of material properties, based on the number of relevant failure modes in the test database. In the last step, the resistance partial factors for models defined in DIN EN 1996‐1‐1/NA and DIN EN 1996‐1‐1/NA – Annex K are calculated by applying the probabilistic methods recommended in EN 1990 – Annex D and the model bias.