Corrosion Behavior of 316LN and 316 Stainless Steels During Long-term Exposure to Aerated 0.5 M NaCl Using Electrochemical Noise Technique

In the present work 316LN as well as 316 stainless steel (SS) coupons each of dimensions (0.025 × 0.018 × 0.006 m³) in well-polished condition were used as two nominal electrodes which were immersed in the aerated solution of 0.5 M NaCl. Correlated current and potential electrochemical noise (EN) signals were collected at 1 Hz sampling frequency for 1 h daily over a period of 30 days. The detrended EN data were used to calculate the noise resistance (R _N) as well as the spectral noise resistance at zero frequency (R _SN^o) values and other statistical parameters. To study the nature of pits and distribution of their diameters as well as depths, extensive observations of the pitted and the blank specimens were carried out using Confocal Laser Scanning Microscopy (CLSM). The current and the potential records of the two alloys showed distinct differences in their corrosion behavior. It was observed that within less than 4 h of immersion, 316SS showed signals indicative of unstable pitting and onset of stable pitting was noticed after 48 h of exposure. However, until about 24 h, 316LN showed just the random signals and unstable pitting was observed after 28 h. The signals clearly indicated continuous growth of the stable pits in 316SS as against the repassivation of the unstable pits in 316LN after 7 days exposure. It was observed that R _N values showed a continuous decrease in the case of 316SS, but were quite stable in the case of 316LN over the exposure period. Concurrent to these observations it was observed that 316SS specimen was extensively pitted. The frequency distributions of pit diameters as well pit depths were observed to be highest at 10-20 μm and 5-10 μm, respectively. However, pits with as large as 70-80 μm diameter and as deep as 20-25 μm too were observed. No pits were observed in case of 316LN even after 30 days of exposure, an observation that corroborates well with the stable R _N values. Thus, in the present investigation, the long-term tests using EN technique coupled with CLSM studies conclusively prove that many unstable pits initiated in 316SS turn into stable ones resulting in insidious localized corrosion attack whereas the unstable pits initiated in 316LN get passivated in the simulated coastal environment.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

A novel sine augmented scaled sine cosine algorithm for frequency control issues of a hybrid distributed two-area power system

Neural Computing and Applications - In this research article, a novel approach is proposed by considering the sine augmented scaled sine cosine (SAS-SCA) Algorithm for the load frequency control of...     

Multi-objective evolutionary algorithm for SSSC-based controller design

In this paper, an evolutionary multi-objective optimization approach is employed to design a static synchronous series compensator (SSSC)-based controller. The design objective is to improve the transient performance of a power system subjected to a severe disturbance by damping the multi-modal oscillations namely; local mode, inter-area mode and inter-plant mode. A genetic algorithm (GA)-based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented and compared with a PI controller under various disturbances namely; three-phase fault, line outage, loss of load and unbalanced faults to show the effectiveness and robustness of the proposed approach.     

LE-SBCC: Loss-Event Oriented Source-Based Multicast Congestion Control

Congestion control is an important building block of a Quality of Service (QoS) system for multicast-based multimedia services and applications on the World Wide Web. We propose an end-to-end single-rate source-based multicast congestion control scheme (LE-SBCC) for reliable or unreliable multicast transport protocols. It addresses all the pieces of the single-rate multicast congestion control problem including drop-to-zero issues, TCP friendliness and RTT estimation. The scheme design consists of a cascaded set of filters and a rate-based additive-increase multiplicative-decrease (AIMD) module. These filters together transform the multicast tree to appear like a unicast path for the purposes of congestion control. Unlike TCP, the scheme is not self-clocked but acts upon a stream of loss indications (LIs) from receivers. These LIs are filtered to get a stream of loss events (LEs) (S. Floyd et al., in SIGCOMM 2000, Aug. 2000) (at most one per RTT per receiver). This LE stream is further filtered to extract the maximum LEs from any one receiver. Then the scheme effects at most one rate-reduction per round trip time (RTT). A range of results (simulation and experimental) is presented and compared against the mathematical model of the scheme components. Furthermore, we have successfully adapted TFRC (Op. cit) to our scheme, which is important to multimedia services desiring relatively stable rates over short time scales.     

Effect of the fabrication method on the electrical properties of poly(acrylonitrile-co-butadiene-co-styrene)/carbon black composites

Poly(acrylonitrile-co-butadiene-co-styrene) (ABS), an engineering plastic, was combined with carbon black (CB) to increase its conductivity. The ABS/CB composites were prepared using two different methods: dissolution of ABS in Butan-2-one and manual mixing of the constituent materials. These fabrication methods led to different microstructures, which led to vastly different electrical properties. The microstructures were acquired using scanning electron microscopy (SEM) and optical microscopy, while the electrical conductivity was obtained using impedance spectroscopy. The percolation threshold of the composites fabricated using the manual mixing method was found to be much lower (0.0054 vol.% CB) than that of the composites fabricated using the dissolution method (2.7 vol.% CB).     

Experimental study of chemical treatment of coal fly ash to reduce the mobility of priority trace elements

Coal fired electric power plants produce large volumes of fly ash and other coal combustion by-products (CCBs) every year. Although almost 50% of the fly ash produced in the US is recycled for beneficial use, most of the ash material is disposed in dry landfills and ash lagoon impoundments. Fly ash may contain hazardous leachable trace elements such as As, B, Cr, Mo, Ni, Se, Sr and V which have a negative impact on the environment due to potential leaching by acid rain and groundwater with time. Many of the older CCB disposal facilities are unlined and unmonitored and as a result the EPA is currently developing national standards for monitoring CCB disposal sites. The cost to the US electric power industry could exceed one billion dollars if existing and closed CCB disposal facilities come under regulation. Thus simple, low-cost and effective in situ chemical treatment techniques are needed to stabilize hazardous leachable trace elements in the coal combustion by-product (CCB) materials. This paper reports the results of experiments designed to chemically treat fly ash with ferrous sulfate solutions to immobilize hazardous leachable trace elements after disposal.The current study is focused on three acidic and one alkaline fly ash samples collected from electric power plants located in the southeastern United States that were treated with two ferrous sulfate treatment solutions. The first treatment solution contained ferrous sulfate (FS) to give 322 mg/L of dissolved iron, while the second treatment solution contained the same concentration of ferrous sulfate along with excess calcium carbonate (FS + CC) to buffer the pH. Fly ash treatment experiments were carried out at solid:liquid (S:L) ratios of 1:3 and 1:30. The effectiveness of the treatment methods was evaluated by sequentially leaching the treated and the untreated fly ash samples using a synthetic acid rain (SAR) solution (US EPA Method 1312B SPLP fluid) as the leachate. The best overall treatment result was shown by the unbuffered ferrous sulfate solution at the 1:30 S:L ratio, which substantially reduced the mobility of the oxyanion trace elements. The overall mobility reduction achieved for As was 23-72%, B mobility was reduced by 43-80%, Cr by 45-77%, Mo by 21-90%, Se by 41-85% and V by 41-53% The unbuffered ferrous sulfate treatment was not effective for immobilization of the cationic trace elements Ni and Sr.     

Hybrid BFOA–PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems

In the bacteria foraging optimization algorithm (BFAO), the chemotactic process is randomly set, imposing that the bacteria swarm together and keep a safe distance from each other. In hybrid bacteria foraging optimization algorithm and particle swarm optimization (hBFOA–PSO) algorithm the principle of swarming is introduced in the framework of BFAO. The hBFOA–PSO algorithm is based on the adjustment of each bacterium position according to the neighborhood environment. In this paper, the effectiveness of the hBFOA–PSO algorithm has been tested for automatic generation control (AGC) of an interconnected power system. A widely used linear model of two area non-reheat thermal system equipped with proportional-integral (PI) controller is considered initially for the design and analysis purpose. At first, a conventional integral time multiply absolute error (ITAE) based objective function is considered and the performance of hBFOA–PSO algorithm is compared with PSO, BFOA and GA. Further a modified objective function using ITAE, damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients is proposed to increase the performance of the controller. Further, robustness analysis is carried out by varying the operating load condition and time constants of speed governor, turbine, tie-line power in the range of +50% to ?50% as well as size and position of step load perturbation to demonstrate the robustness of the proposed hBFOA–PSO optimized PI controller. The proposed approach is also extended to a non-linear power system model by considering the effect of governor dead band non-linearity and the superiority of the proposed approach is shown by comparing the results of craziness based particle swarm optimization (CRAZYPSO) approach for the identical interconnected power system. Finally, the study is extended to a three area system considering both thermal and hydro units with different PI coefficients and comparison between ANFIS and proposed approach has been provided.     

Simulation study for automatic generation control of a multi-area power system by ANFIS approach

This paper deals with the application of artificial neural network (ANN) based ANFIS approach to automatic generation control (AGC) of a three unequal area hydrothermal system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Appropriate generation rate constraints (GRC) have been considered for the thermal and hydro plants. The hydro area is considered with an electric governor and thermal area is considered with reheat turbine. The design objective is to improve the frequency and tie-line power deviations of the interconnected system. 1% step load perturbation has been considered occurring either in any individual area or occurring simultaneously in all the areas. It is a maiden application of ANFIS approach to a three unequal area hydrothermal system with GRC considering perturbation in a single area as well as in all areas. The performance of the ANFIS controller is compared with the results of integral squared error (ISE) criterion based integral controller published previously. Simulation results are presented to show the improved performance of ANFIS controller in comparison with the conventional integral controller. The results indicate that the controllers exhibit better performance. In fact, ANFIS approach satisfies the load frequency control requirements with a reasonable dynamic response.