Dynamic behaviour of material states in steam power plant control

The enormous price increase in petroleum and the limited reserves of other fossil fuels have resulted in the increased use of nuclear power plants for the basic load of electricity supply. Consequently, conventional steam power plants have been used to meet the variable and peak loads in electricity generation. The control of fast and large load changes is becoming more and more important for conventional power plant operations. An economical control of the nonstationary operation (start-up, shut-down and large load changes) is possible only by approaching and maintaining the maximum allowable values of the material state variables (temperature θ, strain ? and stress σ) at the critical points of the power plant components. To achieve this primary control goal, the dynamic behaviour of material states must be well understood. A direct measurement of the changes in material states especially due to thermal stresses, caused by temperature gradients, is not possible. The material states can be calculated, however, by means of mathematical models describing the nonstationary temperature distribution. The working fluid temperature, pressure and mass flow rate are the input variables for these mathematical models. This paper presents a linear mathematical model for the investigation of the dynamic behaviour of material states. Another mathematical model is also developed for calculating the thermal stresses for large temperature and load changes. Thus, the steam generator models so far describing only the states of the working fluid can be extended to the material states. The basic idea is demonstrated for an insulated thick wall tube containing a working fluid. The simulation of the mathematical models is performed.     

A NEW METHOD FOR MACHINING OF ELECTRICALLY NONCONDUCTIVE WORKPIECES USING ELECTRIC DISCHARGE MACHINING TECHNIQUE

In this study, a new method for machining of nonconductive ceramic workpieces in electric discharge machining (EDM) was developed. Machining surfaces of nonconductive workpieces were coated with a conductive layer (CL) and graphite powder was added to dielectric fluid for machining. Al₂O₃, ZrO₂, SiC, B₄C and glass workpiece samples were machined by using the method. Different machining conditions were tested for each sample and optimum machining parameters were determined. Effect of electrical conductivity, thermal conductivity and melting point of workpieces on material removal rate (MRR) was investigated. Optical microscope and SEM (Scanning Electron Microscope) surface photographs of workpieces taken after machining are presented and discussed.     

Hybrid movement strategy in self-orienting directional sensor networks

The coverage problem in directional sensor networks (DSNs) introduces new challenges especially for randomly deployed networks. As many overlapped regions and coverage holes might occur after the initial deployment, self-orientation of the nodes is a necessity for randomly deployed DSNs. There exist two main approaches for the self-orientation of directional sensor nodes in DSNs [1], motility and mobility. Motility refers to the adjustment of the working direction of the nodes, whereas mobility describes the physical movement of the nodes. Most existing studies propose solutions based on the motility capability of the directional sensor nodes. On the other hand, mobility is a powerful feature offering great flexibility. Nevertheless, the high energy consumption of mobility discourages researchers to utilize this approach in their solutions. In this study, we propose a novel approach, a hybrid movement strategy (HMS), where we exploit motility/mobility in a cascaded manner for the coverage improvement in DSNs. The HMS improves the initial coverage up to 47% and achieves up to 7% more coverage than the motility only solution. Besides, it has provided at least 40% energy-saving compared to the mobility only solution in our scenarios.     

LC-ESI-QTOF-MS/MS Analysis,Cytotoxic, Antiviral,Antioxidant, and Enzyme Inhibitory Properties of Four Extracts of Geranium pyrenaicum Burm. f.: A Good Gift from the Natural Treasure

This study focused on the biological evaluation and chemical characterization of Geranium pyrenaicum Burm. f. Different solvent extracts (hexane, ethyl acetate, methanol, and water extracts) were prepared. The phytochemical profile, antioxidant, and enzyme inhibitory activity were investigated. Cytotoxicity was assessed using VERO, FaDu, HeLa and RKO cells. The antiviral activity was carried out against HSV-1 (Herpes simplex virus 1) propagated in VERO cell line. The aqueous extract, possessing high phenolic content (170.50 mg gallic acid equivalent/g extract), showed the highest reducing capacity (613.27 and 364.10 mg Trolox equivalent/g extract, for cupric reducing antioxidant capacity and ferric reducing antioxidant power, respectively), radical scavenging potential (469.82 mg Trolox equivalent/g extract, against 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)), metal chelating ability (52.39 mg ethylenediaminetetraacetic acid equivalent/g extract) and total antioxidant capacity (3.15 mmol Trolox equivalent/g extract). Liquid chromatography-electrospray ionization-quadrupole time-of-flight-mass spectrometry (LC-ESI-QTOF-MS/MS) alloved to tentatively identify a total of 56 compounds in the extracts, including ellagitannins, gallic acid and galloyl derivatives amongst others. The ethyl acetate extracts substantially depressed cholinesterase enzymes (4.49 and 12.26 mg galantamine equivalent/g extract against AChE and BChE, respectively) and α-amylase enzyme (1.04 mmol acarbose equivalent/g extract). On the other hand, the methanolic extract inhibited tyrosinase (121.42 mg kojic acid equivalent/g extract) and α-glucosidase (2.39 mmol acarbose equivalent/g extract) activities. The highest selectivity towards all cancer cell lines (SI 4.5–10.8) was observed with aqueous extract with the FaDu cells being the most sensitive (CC₅₀ 40.22 µg/mL). It can be concluded that the presence of certain bioactive antiviral molecules may be related to the high anti HSV-1 activity of the methanolic extract. This work has generated vital scientific data on this medicinal plant, which is a prospective candidate for the creation of innovative phyto-pharmaceuticals.     

Operational Conditions of Activated Sludge: Influence on Flocculation and Dewaterability

Selected operational conditions of activated sludge are investigated in relation to their effect on flocculation and dewatering. Semi-continuous reactors with 2 -L volume were operated at different mean cell residence times, C/N ratios, and three different influent cations. Results show that MCRT, C/N ratio, and the cation type affect the bioflocculation capacity of activated sludge measured by the quantity of extracellular polymeric substances. As the MCRT value operated in the reactors and the C/N ratio of the influent wastewater increase, total amount of polymers produced increases. High MCRT values and low C/N values cause good dewatering of the sludge. All cations are shown to stimulate the EPS production in a way that the highest total EPS concentrations are observed at the highest cation dosages. The dewaterability of the sludges improves only with increasing calcium and magnesium concentrations and deteriorates with increasing potassium concentration.     

Fatty Acid Composition,Total Sugar Content and Anti-Diabetic Activity of Methanol and Water Extracts of Nine Different Fruit Tree Leaves Collected from Mediterranean Region of Turkey

In this research, the total sugar content, fatty acid compositions, and α-amylase and α-glucosidase inhibitory activity of methanolic and water extracts of nine different fruit tree leaves were determined. α-amylase and α-glycosidase inhibitory activity were determined by using Caraway-Somogyi iodine/potassium iodide and 4-nitrophenyl-α-D-glucopyranoside as substrate, respectively. The total sugar content of the nine different fruit tree leaves varies from 281.02 mg GE/g (glucose equivalents) to 643.96 mg GE/g. Methanolic extract from avocado leaves had the strongest in α-amylase and α-glucosidase inhibitory activity, 69.21 and 96.26%, respectively. Fatty acid composition of nine fruit tree leaves was characterized by gas chromatography and 24 components were identified. Among the tested fruit tree leaves, the main component was linolenic acid (49.09%). The level of essential fatty acids are over 50% in mulberry, grape, and loquat leaves. Polyunsaturated fatty acids were the major group of fatty acids present in oils of mulberry, fig, pomegranate, grape, and loquat leaves. Therefore, these oils can be considered as a good source of polyunsaturated fatty acids. Furthermore, avocado can be regarded as a new source for diabetic therapies.     

A variable neighborhood search for minimizing total weighted tardiness with sequence dependent setup times on a single machine

This paper deals with the single machine scheduling problem to minimize the total weighted tardiness in the presence of sequence dependent setup. Firstly, a mathematical model is given to describe the problem formally. Since the problem is NP-hard, a general variable neighborhood search (GVNS) heuristic is proposed to solve it. Initial solution for the GVNS algorithm is obtained by using a constructive heuristic that is widely used in the literature for the problem. The proposed algorithm is tested on 120 benchmark instances. The results show that 37 out of 120 best known solutions in the literature are improved while 64 instances are solved equally. Next, the GVNS algorithm is applied to single machine scheduling problem with sequence dependent setup times to minimize the total tardiness problem without changing any implementation issues and the parameters of the GVNS algorithm. For this problem, 64 test instances are solved varying from small to large sizes. Among these 64 instances, 35 instances are solved to the optimality, 16 instances' best-known results are improved, and 6 instances are solved equally compared to the best-known results. Hence, it can be concluded that the GVNS algorithm is an effective, efficient and a robust algorithm for minimizing tardiness on a single machine in the presence of setup times.     

Discrete approximation heuristics for the capacitated continuous location–allocation problem with probabilistic customer locations

The capacitated continuous location–allocation problem, also called capacitated multisource Weber problem (CMWP), is concerned with locating m facilities in the Euclidean plane, and allocating their capacity to n customers at minimum total cost. The deterministic version of the problem, which assumes that customer locations and demands are known with certainty, is a nonconvex optimization problem. In this work, we focus on a probabilistic extension referred to as the probabilistic CMWP (PCMWP), and consider the situation in which customer locations are randomly distributed according to a bivariate probability distribution. We first formulate the discrete approximation of the problem as a mixed-integer linear programming model in which facilities can be located on a set of candidate points. Then we present three heuristics to solve the problem. Since optimal solutions cannot be found, we assess the performance of the heuristics using the results obtained by an alternate location–allocation heuristic that is originally developed for the deterministic version of the problem and tailored by us for the PCMWP. The new heuristics depend on the evaluation of the expected distances between facilities and customers, which is possible only for a few number of distance function and probability distribution combinations. We therefore propose approximation methods which make the heuristics applicable for any distance function and probability distribution of customer coordinates.