Impact of communication time delays on combined LFC and AVR of a multi-area hybrid system with IPFC-RFBs coordinated control strategy

In this paper, the impact of communication time delays (CTDs) on combined load frequency control (LFC) and automatic voltage regulation (AVR) of a multi-area system with hybrid generation units is addressed. Investigation reveals that CTDs have significant effect on system performance. A classical PID controller is employed as a secondary regulator and its parametric gains are optimized with a differential evolution - artificial electric field algorithm (DE-AEFA). The superior performance of the presented algorithm is established by comparing with various optimization algorithms reported in the literature. The investigation is further extended to integration of redox flow batteries (RFBs) and interline power flow controller (IPFC) with tie-lines. Analysis reveals that IPFC and RFBs coordinated control enhances system dynamic performance. Finally, the robustness of the proposed control methodology is validated by sensitivity analysis during wide variations of system parameters and load.     

Study on ketalization reaction of poly(vinyl alcohol) by ketones. IV. Reaction between poly(vinyl alcohol) and aliphatic ketones and behavior of polyvinylketal in water

Ketalization reaction of poly(vinyl alcohol) (PVA) by aliphatic ketones, dimethylsulfoxide (DMSO) as solvent, under the presence of acidic catalyst, in homogeneous system was carried out and the synthesis of polyvinylketals were successfully performed. The equilibrium constant at 40°C is ca. 0.07 in the case of methyl n-propyl ketone (nPK) and methyl n-butyl ketone (nBK), but is ca. 0.05 in the case of methyl i-propyl ketone (iPK) and ca. 0.01 in the case of methyl i-butyl ketone (iBK) and methyl t-butyl ketone (tBK), respectively. Moreover, the ketalization degree of polyvinylketal by iBK and tBK reached to only ca. 35 mol % as the maximum. It seems that these were due to steric hindrance of bulky side chain of ketones. But the heat of reaction is 7.5 kcal/mol in all aliphatic ketones, it seems to proceed the same ketalization reaction mechanism. Films prepared from the polyvinylketals were soaked in water and degree of swelling, solubility, and hydrolysis of films were measured. The reaction of film with water, in acidic side, at first the film swells, and then, as the deketalization reaction proceeds, the film dissolves in water. The dissolution time is controlled by the kind of ketones, ketalization degree, and pH of water which reveals that deketalization reaction proceeds proportional to proton concentration. It is more difficult to dissolve highly ketalized polyvinylketals obtained by propyl ketones and butyl ketones than that by acetone. The hydrolysis of polyvinylketal film proceeds in the order as follows: acetone > MEK > nPK > iPK ≒ nBK > iBK > tBK. This phenomenon seems to be affected by hydrophobicity of the film surface which depends upon the kind of the original ketones.     

Stochastic Resonance in Recurrent Neural Network with Hopfield-Type Memory

Stochastic resonance (SR) is known as a phenomenon in which the presence of noise helps a nonlinear system in amplifying a weak (under barrier) signal. In this paper, we investigate how SR behavior can be observed in practical autoassociative neural networks with the Hopfield-type memory under the stochastic dynamics. We focus on SR responses in two systems which consist of three and 156 neurons. These cases are considered as effective double-well and multi-well models. It is demonstrated that the neural network can enhance weak subthreshold signals composed of the stored pattern trains and have higher coherence abilities between stimulus and response.     

Optimizing latency and throughput of application workflows on clusters

Scheduling, in many application domains, involves optimization of multiple performance metrics. For example, application workflows with real-time constraints have strict throughput requirements and also desire a low latency or response time. In this paper, we present a novel algorithm for the scheduling of workflows that act on a stream of input data. Our algorithm focuses on the two performance metrics, latency and throughput, and minimizes the latency of workflows while satisfying strict throughput requirements. We also describe steps to use the above approach to solve the problem of meeting latency requirements while maximizing throughput. We leverage pipelined, task and data parallelism in a coordinated manner to meet these objectives and investigate the benefit of task duplication in alleviating communication overheads in the pipelined schedule for different workflow characteristics. The proposed algorithm is designed for a realistic bounded multi-port communication model, where each processor can simultaneously communicate with at most k distinct processors. Experimental evaluation using synthetic benchmarks as well as those derived from real applications shows that our algorithm consistently produces lower latency schedules that meet throughput requirements, even when previously proposed schemes fail.     

Enhanced catalytic activity of nanoshell carbon co-doped with boron and nitrogen in the oxygen reduction reaction

The use of carbon cathode catalysts in polymer electrolyte fuel cells instead of the current platinum catalysts is attracting increasing attention. We claim that two factors are important for enhancing the activity of carbon cathode catalysts in the oxygen reduction reaction (ORR): the formation of a nanoshell structure and co-doping with boron and nitrogen. Herein, we investigate the preparation and characterization of active ORR carbon catalysts that combine the above factors. Boron and nitrogen (BN)-doped nanoshell-containing carbon (BN-NSCC) was prepared by carbonizing a mixture of poly(furfuryl alcohol), cobalt phthalocyanine, melamine, and a trifluoroborane–methanol complex at 1000 °C. Transmission electron microscopy and X-ray photoelectron spectroscopy revealed the formation of nanoshell structures with distorted graphitic layers and the introduction of boron and nitrogen atoms, respectively. The ORR activity was evaluated in oxygen-saturated 0.5 mol dm^?3 H₂SO₄ using Koutecky–Levich analysis. The BN-NSCC showed an eight to ten times higher ORR activity than undoped NSCC, with an increased number of electrons participating in the reaction. Tafel analysis revealed a change in the rate-determining step caused by BN-doping. Thus, the combination of a nanoshell structure and co-doping with boron and nitrogen was found to improve the ORR activity of carbon catalysts.     

Insulating and Other Physical Properties of CoO‐Doped Zinc Oxyfluoride‐Borate Glass‐Ceramics

Zinc oxy fluoro borate glasses mixed with different concentrations of CoO (ranging from 0 to 2.0 mol%) are synthesized and subsequently crystallized. The scanning electron microscopy pictures have exhibited crystallinity. Differential scanning calorimetric studies have indicated that the prepared samples consist of multiple crystal phases. The X‐ray diffraction patterns have indicated that the glass‐ceramic samples are composed of αZn(BO₂)_2, (Zn)₃(BO₃)_2, CoF₂, CoF₃, Co₃FB₇O₁₃, ZnCo₂O₄, Co₃O₄ crystalline phases. The optical absorption and photoluminescence studies have indicated that there is a gradual increase of tetrahedral cobalt ion concentration with increase of CoO concentration in the glass network. IR spectroscopic studies have pointed out increased degree of polymerization of the zinc oxy fluoro borate glass network with increase of CoO content. The analysis of results of dielectric properties indicated increase of insulating strength of the glass‐ceramics with increase of CoO content. Finally, the dielectric breakdown strength of the samples is measured at room temperature in air medium and it is found to increase from 12.9 to 19.2 kV/cm with increase of CoO from 0.2 to 2.0 mol%. The reasons for such increase of breakdown strength are discussed quantitatively in terms of dielectric parameters with aid of data on spectroscopic properties.     

Evaluating thermal and thermooxidation stability for lubricating oils via microscale methods

Differential thermal analysis (DTA) and thermogravimetry (TG) methods have been developed to evaluate the thermal and thermooxidation stability of different lubricating oils. Measurements are carried out either by heating the oil sample at a constant rate (direct programme) or by keeping it at a fixed high temperature (isothermal programme). Oxygen at a constant flow rate is used for thermooxidation measurements. Tested samples included different viscosity grades: neutral base oils, unadditivated lubricating oil blends, and industrial oils. The mechanism of thermal decomposition for ZDDP and the estimation of its optimum concentration was also considered.     

Degradation of cyanuric acid in soil by Pseudomonas sp. NRRL B-12227 using bioremediation with self-immobilization system

The rates of degradation of cyanuric acid, a key intermediate in a metabolic pathway of s-triazine herbicides, were measured for Pseudomonas sp. NRRL B-12227. The rate of degradation was affected by the rate of cyanuric acid transport through cell membranes and the activity of cyanuric acid amidohydrolase inside the cells. At low concentrations of cyanuric acid, the acclimation of cells to cyanuric acid and/or added nutrients effectively enhanced the degradation rate. The strain was also applied to bioremediation using a Bioremediation with Self-Immobilization System (BSIS), in which Pseudomonas sp. NRRL B-12227 cells were co-immobilized with Bacillus subtilis, the latter of which secretes a viscous polymer, in a shallow layer of soil packed in a column. More than 70% of the Pseudomonas sp. NRRL B-12227 cells were co-immobilized with the B. subtilis in a 7.5 cm layer of the packed soil by self-aggregation. More than 60% of the 1 mM cyanuric acid supplied to the packed soil was degraded in this layer during a 72 h period.     

An improved damage diagnostic technique based on Singular Spectrum Analysis and time series models

An approach to enhance the sensitivity of the damage index using the prediction errors of autoregressive – autoregressive exogenous models by augmenting Singular Spectrum Analysis (SSA) to detect and locate minor damage is presented. Numerical simulation studies are carried out by considering a simply supported beam with single and multiple cracks. An experimental study on a reinforced cement concrete beam has been carried out to validate the technique using different levels of damage. The studies emphasise that the SSA improves the sensitivity of the damage index for detection and also localisation, handling environmental/operational variability and measurement noise.