Investigation into the effect of carboxylic acid monomer on particle nucleation and growth in emulsifier-free emulsion copolymerization of styrene-butadiene-acrylic acid

Latexes of carboxylated styrene-butadiene rubber were prepared via batch emulsion copolymerization with different amounts of acrylic acid in the absence of emulsifier. The effect of acid monomer was investigated in the particle formation and growth. It was observed that the amount of acrylic acid strongly affected the particle formation. The number of particles and thus polymerization rate increased with increasing of the acid content. There was no significant difference in the polymerization rate per particle in all experiments. The results show that in this case particle growth process is less dependent on the acrylic acid amount in comparison with its influence on nucleation stage and then particle number. Several parameters such as polymerization rate and number of latex particle per unit volume of the aqueous phase were calculated. Attempt was made to evaluate the average number of growing chain per particle. Also average particle diameter of the above carboxylated SBR latexes was obtained through some calculations from the direct measurement of average particle diameter in the swollen state by light scattering technique for the first time.     

Relating Sediment Yield Estimations to the Wet Front Term Using Rainfall Simulator Field Experiments

Water Resources Management - Depth to wet front is generally considered as the amount of water that penetrates into soil and wets the internal soil layer. This is an important variable especially...     

Knowledge Diffusion of the Internet of Things (IoT): A Main Path Analysis

Wireless Personal Communications - The Internet of Things (IoT) is a concept that has attracted significant attention since the emergence of wireless technology. The knowledge diffusion of IoT...     

Modeling industrial thickener using computational fluid dynamics (CFD), a case study: Tailing thickener in the Sarcheshmeh copper mine

Separation of particles from liquid in the large gravitational tanks is widely used in mining and industrial wastewater treatment process. Thickener is key unit in the operational processes of hydrometallurgy and is used to separate solid from liquid. In this study, population balance models were combined with computational fluid dynamics (CFD) for modeling the tailing thickener. Parameters such as feed flow rate, flocculant dosage, inlet solid percent and feedwell were investigated. CFD was used to simulate the industrial tailing thickener with settled bed of 120 m diameter which is located in the Sarcheshmeh copper mine. Important factor of drag force that defines the rake torque of rotating paddles on the bed was also determined. Two phases turbulence model of Eulerian/Eulerian in accordance with turbulence model of k-ε was used in the steady-state. Also population balance model consists of 15 groups of particle sizes with Luo and Lehr kernel was used for aggregation/breakage kernel. The simulation results showed good agreement with the operational data.     

Effect of galvanic contact on the flotability of galena in the presence and absence of a collector

In this paper, the effect of various electrochemical environments in the galena flotation is investigated. The electrochemical environments consisted of a ball mill for grinding of galena ore and a Denver flotation cell for flotation of galena in the laboratory scale. In order to achieve the maximum recovery with sodium hyposulfite, the concentrations of 0.06 and 0.12 M of air and nitrogen gases have been used to control the pulp potential in the Denver flotation cell. The galena sample was from the “Era mine” which is located in the Kiyasar area, north of Iran. This mine contains: Galena (PbS) at least 22%, Fluorite (CaF₂) 73.37%, Quartz (SiO₂) 2.54% and other minerals such as Cerussite (PbCO₃) and Kaolinite (Al₂Si₂O₅(OH)₄). Flotation of Galena was conducted in a 0.12 M of sodium hyposulfite solution. It was found that the amount of recovery by this process was 85% and 63% in the presence and absence of potassium amyl xanthate (KAX) and at an estimated potential of 280 to 350 mV respectively while the recovery was 70% and 52% at an approximate potential of 175 to 210 mV in water in the presence and absence of collector (KAX).     

A high-performance and scalable multi-core aware software solution for network monitoring

In recent years, the need for high-performance network monitoring tools, which can cope with rapidly increasing network bandwidth, has become vital. A possible solution is to utilize the processing power of multi-core processors that nowadays are available as commercial-off-the-shelf (COTS) hardware. In this paper, we introduce a software solution for wire-speed packet capturing and transmission for TCP/IP networks under Linux operating system, called DashCap. The results of our experimental evaluations show that the proposed solution causes more than two times performance boost for packet capturing in comparison to the existing software solutions under Linux. We have proposed a scalable software architecture for network monitoring tools called DashNMon, which is based on DashCap. Multi-core awareness is a distinguished property of this architecture. Comparing to the existing cluster-based solutions, DashNMon can be used with COTS multi-core processors. In order to evaluate the proposed solutions, we have developed several prototype tools. The results of the experiments carried out using these tools show the scalability and high performance of the network monitoring tools that are based on the proposed architecture. Using the proposed architecture, it is possible to design and implement high-performance multi-threaded network intrusion detection systems (NIDSs) or application-layer firewalls, completely in the user space and with better utilization of the computational resources of multi-processor/multi-core systems.     

Stable identification of nonlinear systems using neural networks: theory and experiments

This paper presents an approach for stable identification of multivariable nonlinear system dynamics using a multilayer feedforward neural network. Unlike most of the previous neural network identifiers, the proposed identifier is based on a nonlinear-in-parameters neural network (NLPNN). Therefore, it is applicable to systems with higher degrees of nonlinearities. Both parallel and series-parallel models are used with no a priori knowledge about the system dynamics. The method can be considered both as an online identifier that can be used as a basis for designing a neural network controller as well as an offline learning scheme for monitoring the system states. A novel approach is proposed for the weight updating mechanism based on the modification of the backpropagation (BP) algorithm. The stability of the overall system is shown using Lyapunov's direct method. To demonstrate the performance of the proposed algorithm, an experimental setup consisting of a three-link macro-micro manipulator (M/sup 3/) is considered. The proposed approach is applied to identify the dynamics of the experimental robot. Experimental and simulation results are given to show the effectiveness of the proposed learning scheme.     

Thermo-mechanical vibration analysis of rotating nonlocal nanoplates applying generalized differential quadrature method

In this study, thermal and small-scale effects on the flapwise bending vibrations of a rotating nanoplate, which can be the basis of nano-turbine design, have been analyzed. The nano-turbine is made of an orthotropic nanoplate with a setting angle that is modeled based on the classical plate theory (CPT) with cantilever boundary conditions. The axial forces are also included in the model as the true spatial variation due to the rotation and temperature change. The governing equations and boundary conditions are derived according to Hamilton's principle and the governing equations are solved with the aid of the generalized differential quadrature method. The effects of small-scale parameter, nondimensional angular velocity, temperature change, and setting angles in the first four nondimensional frequencies are discussed. Due to the consideration of the rotating effects, results of this study are applicable in nano-machines, such as nano-motors, nano-rotor, and other rotating nano-structures. Also, by considering the effect of thermal loading on rotation of a nanoplate, the results are useful in the design of nano-turbines.     

Acoustic damping flexible polyurethane foams: Effect of isocyanate index and water content on the soundproofing

High-efficiency sound absorbing flexible polyurethane foams (FPUFs) are manufactured using nonpolar polyester resin, methylene diphenyl diisocyanate, and other reagents by one-shot bulk polymerization. In this study, the impact of the isocyanate index (90, 100, and 110) and water content (2.5 and 5%) on the microphase separation and soundproofing behavior of FPUFs are examined using atomic force microscopy, Fourier transform infrared spectroscopy, optical microscope, and an impedance tube device. The results reveal that the increase of the isocyanate index and water content leads to the increase of the cell size, cell size distribution, open-cell content, cell wall roughness, and microphase separation. Also, maximum sound absorption coefficient (α) reaches to 0.98 and the average of α in the frequency range of 1500–4000 Hz increases from 0.7 to 0.87 by increasing the water content from 2.5 to 5% and isocyanate index from 90 to 110; therefore, acoustic damping performance enhances up to 26.24% due to the synergic effects of microphase separation on the viscose media formation, open-cell content, cell wall roughness, cell size, and cell size distribution. In conclusion, FPUFs with an optimal amount of microphase separation and drainage flow can be a promising candidate for sound insulating materials. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47363.     

Modified Cuckoo Optimization Algorithm (MCOA) to solve Precedence Constrained Sequencing Problem (PCSP)

In recent years, new meta-heuristic algorithms have been developed to solve optimization problems. Recently-introduced Cuckoo Optimization Algorithm (COA) has proven its excellent performance to solve different optimization problems. Precedence Constrained Sequencing Problem (PCSP) is related to locating the optimal sequence with the shortest traveling time among all feasible sequences. The problem is motivated by applications in networks, scheduling, project management, logistics, assembly flow and routing. Regarding numerous practical applications of PCSP, it can be asserted that PCSP is a useful tool for a variety of industrial planning and scheduling problems. However it can also be seen that the most approaches may not solve various types of PCSPs and in related papers considering definite conditions, a model is determined and solved. In this paper a new approach is presented for solving various types of PCSPs based on COA. Since COA at first was introduced to solve continuous optimization problems, in order to demonstrate the application of COA to find the optimal sequence of the PCSP, some proposed schemes have been applied in this paper with modifications in operators of the basic COA. In fact due to the discrete nature and characteristics of the PCSP, the basic COA should be modified to solve PSCPs. To evaluate the performance of the proposed algorithm, at first, an applied single machine scheduling problem from the literature that can be formulated as a PCSP and has optimal solution is described and solved. Then, several PCSP instances with different sizes from the literature that do not have optimal solutions are solved and results are compared to the algorithms of the literature. Computational results show that the proposed algorithm has better performance compared to presented well-known meta-heuristic algorithms presented to solve various types of PCSPs so far.