Influence of nanoclay on urea–glyoxalated lignin–formaldehyde resins for wood adhesive

In this research, the influence of nanoclay on urea–glyoxalated lignin–formaldehyde (GLUF) resin properties has been investigated. To prepare the GLUF resin, glyoxalated soda baggase lignin (15 wt%) was added as an alternative for the second urea during the UF resin synthesis. The prepared GLUF resin was mixed with the 0.5%, 1%, and 1.5% nanoclay by mechanically stirring for 5 min at room temperature. The physicochemical properties of the prepared resins were measured according to standard methods. Then the resins were used in particleboard production and the physical and mechanical properties of the manufactured panels were determined. Finally, from the results obtained, the best prepared resin was selected and its properties were analyzed by differential scanning calorimetry (DSC), Fourier transform infrared spectrometry (FTIR), and X-ray diffractometry (XRD). Generally the results indicated that the addition of sodium-montmorillonite (NaMMT) up to 1.5% appears to improve the performance of GLUF resins in particleboards. The results also showed that nanoclays improved mechanical strength (modulus of elasticity (MOE), Modulus of Rupture (MOR), and internal bond (IB) strength) of the panels bonded with GLUF resins. The panels containing GLUF resin and nanoclay yielded lower formaldehyde emission as well as water absorption content than those made from the neat GLUF resins. XRD characterization indicated that NaMMT only intercalated when mixed with GLUF resin. Based on DSC results, the addition of NaMMT could accelerate the curing of GLUF resins. The enthalpy of the cure reaction (ΔH) of GLUF resin containing NaMMT was increased compared with neat GLUF resin. Also the results of FTIR analysis indicated that addition of NaMMT change the GLUF resins structures.     

Rheological and mechanical properties of composites made from wood flour and recycled LDPE/HDPE blend

The effect of compounding method is studied with respect to the rheological behavior and mechanical properties of composites made of wood flour and a blend of two main components of plastics waste in municipal solid waste, low-density polyethylene (LDPE) and high-density polyethylene (HDPE). The effects of recycling process on the rheological behavior of LDPE and HDPE blends were investigated. Initially, samples of virgin LDPE and HDPE were thermo-mechanically degraded twice under controlled conditions in an extruder. The recycled materials and wood flour were then compounded by two different mixing methods: simultaneous mixing of all components and pre-mixing, including the blending of polymers in molten state, grinding and subsequent compounding with wood flour. The rheological and mechanical properties of the LDPE/HDPE blend and resultant composites were determined. The results showed that recycling increased the complex viscosity of the LDPE/HDPE blend and it exhibited miscible behavior in a molten state. Rheological testing indicated that the complex viscosity and storage modulus of the composites made by pre-mixing method were higher than that made by the simultaneous method. The results also showed that melt pre-mixing of the polymeric matrix (recycled LDPE and HDPE) improved the mechanical properties of the wood–plastic composites.     

Exact stability of a platoon of vehicles by considering time delay and lag

The problem of controlling a string of vehicles moving in one dimension is considered so that they all follow a lead vehicle with constant time headway spacing between successive vehicles. Due to realistic design and execution, the negative effect of the tracking lag parameter and time delay is taken into account. By applying an acceleration feedforward, the distance error of each vehicle will be independent of the behavior of other vehicles. As a result, the vehicle is better able to track a desired trajectory, which improves the string stability. Cluster treatment of characteristic roots (CTCR) paradigm is utilized to reveal the stabilizing parametric regions in the domain of the time delay to render the stability of closed loop system. The string stability analysis is performed to evaluate the disturbance attenuation. Finally, an example of multiple vehicle platoon control is presented, which demonstrates the effectiveness of the proposed method.     

Impacts of automatic control systems of loop restoration scheme on the distribution system reliability

Loop restoration scheme (LRS) is a special feeder automation (FA) scheme, which is used by utilities to improve distribution system reliability. The LRS is controlled and managed by its automatic control system (ACS). The impacts on distribution system reliability indices of implementing LRS mainly depend on the type of its ACS. Two common types of ACS of LRS are presented and used in this study. Successful operation of ACS is dependent on the protection and automatic control functions of switching devices of LRS. Different failure modes of these switching devices can therefore affect the procedure of ACS in fault detecting, isolating and service restoration. The impacts of failure of protection and automatic control functions of switching devices and fuse of lateral distributors on reliability indices are illustrated. The worth of implementing LRS and its ACS type is represented by the reduction in expected customer interruption cost. A distribution test system is utilised to examine the impacts of two common types of ACS of LRS on the distribution system reliability. Selecting the type of ACS of LRS by utilities relies on the desired level of load-point and system reliability improvement. This study aims to quantitatively assess the impacts of two common types of ACS of LRS on the distribution system reliability.     

Effect of ionic strength on the reactivity ratios of acrylamide/acrylic acid (sodium acrylate) copolymerization

The ionic strength (IS) of polyelectrolyte solutions plays an important role in influencing reaction kinetics. The largely unstudied effect of IS on monomer reactivity ratios and copolymerization rates of acrylamide (AAm) and acrylic acid (AAc), in the form of sodium acrylate (NaAc), is investigated. Salt addition affects the nature of overall charges of the polyelectrolyte solution and diminishes the electrostatic repulsions between reacting chains. Therefore, changing the IS of the solution by incorporating salts affect not only the point estimates of the monomer reactivity ratios but also the overall behavior of the copolymerization (with a transition to azeotropic behavior). Experimental results on copolymerization rates confirm the observed trends in reactivity ratio behavior. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40949.     

Perceiving,learning, and exploiting object affordances for autonomous pile manipulation

Autonomous manipulation in unstructured environments will enable a large variety of exciting and important applications. Despite its promise, autonomous manipulation remains largely unsolved. Even the most rudimentary manipulation task—such as removing objects from a pile—remains challenging for robots. We identify three major challenges that must be addressed to enable autonomous manipulation: object segmentation, action selection, and motion generation. These challenges become more pronounced when unknown man-made or natural objects are cluttered together in a pile. We present a system capable of manipulating unknown objects in such an environment. Our robot is tasked with clearing a table by removing objects from a pile and placing them into a bin. To that end, we address the three aforementioned challenges. Our robot perceives the environment with an RGB-D sensor, segmenting the pile into object hypotheses using non-parametric surface models. Our system then computes the affordances of each object, and selects the best affordance and its associated action to execute. Finally, our robot instantiates the proper compliant motion primitive to safely execute the desired action. For efficient and reliable action selection, we developed a framework for supervised learning of manipulation expertise. To verify the performance of our system, we conducted dozens of trials and report on several hours of experiments involving more than 1,500 interactions. The results show that our learning-based approach for pile manipulation outperforms a common sense heuristic as well as a random strategy, and is on par with human action selection.     

An extended compromise ratio method for fuzzy group multi-attribute decision making with SWOT analysis

The technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi-attribute decision making (MADM) method that is used to identify the most attractive alternative solution among a finite set of alternatives based on the simultaneous minimization of the distance from an ideal solution (IS) and the maximization of the distance from the nadir solution (NS). We propose an alternative compromise ratio method (CRM) using an efficient and powerful distance measure for solving the group MADM problems. In the proposed CRM, similar to TOPSIS, the chosen alternative should be simultaneously as close as possible to the IS and as far away as possible from the NS. The conventional MADM problems require well-defined and precise data; however, the values associated with the parameters in the real-world are often imprecise, vague, uncertain or incomplete. Fuzzy sets provide a powerful tool for dealing with the ambiguous data. We capture the decision makers’ (DMs’) judgments with linguistic variables and represent their importance weights with fuzzy sets. The fuzzy group MADM (FGMADM) method proposed in this study improves the usability of the CRM. We integrate the FGMADM method into a strengths, weaknesses, opportunities and threats (SWOT) analysis framework to show the applicability of the proposed method in a solar panel manufacturing firm in Canada.     

New measures for comparing optimization algorithms on dynamic optimization problems

Dynamic optimization problems have emerged as an important field of research during the last two decades, since many real-world optimization problems are changing over time. These problems need fast and accurate algorithms, not only to locate the optimum in a limited amount of time but also track its trajectories as close as possible. Although lots of research efforts have been given in developing dynamic benchmark generator/problems and proposing algorithms to solve these problems, the role of numerical performance measurements have been barely considered in the literature. Several performance criteria have been already proposed to evaluate the performance of algorithms. However, because they only take confined aspects of the algorithms into consideration, they do not provide enough information about the effectiveness of each algorithm. In this paper, at first we review the existing performance measures and then we present a set of two measures as a framework for comparing algorithms in dynamic environments, named fitness adaptation speed and alpha–accuracy. A comparative study is then conducted among different state-of-the-art algorithms on moving peaks benchmark via proposed metrics, along with several other performance measures, to demonstrate the relative advantages of the introduced measures. We hope that the collected knowledge in this paper opens a door toward a more comprehensive comparison among algorithms for dynamic optimization problems.