Modelling of evaporation from the reservoir of Yuvacik dam using adaptive neuro-fuzzy inference systems

Adaptive neuro-fuzzy inference system (ANFIS) models are proposed as an alternative approach of evaporation estimation for Yuvacik Dam. This study has three objectives: (1) to develop ANFIS models to estimate daily pan evaporation from measured meteorological data; (2) to compare the ANFIS model to the multiple linear regression (MLR) model; and (3) to evaluate the potential of ANFIS model. Various combinations of daily meteorological data, namely air temperature, relative humidity, solar radiation and wind speed, are used as inputs to the ANFIS so as to evaluate the degree of effect of each of these variables on daily pan evaporation. The results of the ANFIS model are compared with MLR model. Mean square error, average absolute relative error and coefficient of determination statistics are used as comparison criteria for the evaluation of the model performances. The ANFIS technique whose inputs are solar radiation, air temperature, relative humidity and wind speed, gives mean square errors of 0.181 mm, average absolute relative errors of 9.590% mm, and determination coefficient of 0.958 for Yuvacik Dam station, respectively. Based on the comparisons, it was found that the ANFIS technique could be employed successfully in modelling evaporation process from the available climatic data.     

Brown�CRobinson method for interval matrix games

In this paper, two-person interval matrix games are considered, and by means of acceptability index, Brown–Robinson method to find a mixed-strategy equilibrium is adapted to interval matrix games. Numerical examples are also given.     

Parallel machine scheduling with flexible resources

Parallel machine flexible resource scheduling (PMFRS) problems consider an additional flexible resource (e.g. operators), which can be freely allocated to any jobs and/or any machines and may speed-up the process in proportion to its amount. If job–machine assignment is unspecified, the problem is referred to as unspecified PMFRS (UPMFRS). This paper reviews the mathematical models of both PMFRS and UPMFRS problems in the literature and not only gives some extensions to the model of dynamic PMFRS problem but also presents integer programming (IP) models for static and dynamic UPMFRS problems with the objective of minimizing makespan. To solve large-sized dynamic PMFRS and UPMFRS problems, a relaxed IP based constraint programming (CP) approach is also proposed. All IP models and the proposed IP/CP approach are tested with an extensive computational study. The results of the computational experiments are discussed with respect to the major parameters of the problem and conclusions are drawn.     

Adsorption of malachite green onto bentonite: Equilibrium and kinetic studies and process design

The adsorption of malachite green onto bentonite in a batch adsorber has been studied. The effects of contact time, initial pH and initial dye concentration on the malachite green adsorption by the bentonite have been studied. Malachite green removal was seen to increase with increasing contact time until equilibrium and initial dye concentration, and the adsorption capacity of bentonite was independent of initial pH in the range 3–11. Four kinetic models, the pseudo first- and second-order equations, the Elovich equation and the intraparticle diffusion equation, were selected to follow the adsorption process. Kinetic parameters; rate constants, equilibrium adsorption capacities and correlation coefficients, for each kinetic equation were calculated and discussed. It was shown that the adsorption of malachite green onto bentonite could be described by the pseudo second-order equation. The experimental isotherm data were analyzed using the Langmuir, Freundlich, Temkin and Dubinin–Radushkevich equations. Adsorption of malachite green onto bentonite followed the Langmuir isotherm. The thermodynamic parameters, such as ΔH, ΔS and ΔG, were also determined and evaluated. A single stage batch adsorber was designed for different adsorbent mass/treated effluent volume ratios using the Langmuir isotherm.     

Photocatalytic degradation of Remazol Red F3B using ZnO catalyst

The photocatalytic degradation of aqueous solution of a commercial azo-reactive textile dye, Remazol Red F3B, has been investigated in a batch slurry reactor, in the presence of ZnO catalyst using two different UV light sources emitting at 254 nm and 365 nm. The effects of various process variables on degradation performance of the process have been investigated. The results showed that decolourization and total organic carbon (TOC) removal are both affected in the same manner by the solution pH in the pH range 6-10, showing maxima at pH 7 and pH 10. They are inversely related to the dye concentration, they increase in power-law with the light intensity. Decolourization is faster with 365 nm UV. TOC removal is not affected by UV wavelength in the initial period up to 20 min, after which it progresses faster under 365 nm UV radiation. These results indicate that the UV wavelength influences especially the degradation rate of the intermediate products generated during the initial period of the photocatalytic process. Finally, catalyst loading affects both efficiencies in the same trend, which are maximized at about 2 g/l catalyst loading.     

Scale-up studies for stable,long-term indoor and outdoor production of hydrogen by immobilized Rhodobacter capsulatus

Photofermentative hydrogen production by immobilized Rhodobacter capsulatus YO3 was carried out in a novel photobioreactor in sequential batch mode under indoor and outdoor conditions. Long-term H₂ production was realized in a 1.4 L photobioreactor for 64 days using Rhodobacter capsulatus YO3 immobilized with 4% (w/v) agar on 5 mM sucrose and 4 mM glutamate. The highest hydrogen yield (19 mol H₂/mol sucrose) and hydrogen productivity (0.73 mmol H₂ L^?1 h^?1) were achieved indoors on 5 mM sucrose. The effect of initial sucrose concentration (5 mM, 10 mM, and 20 mM) on hydrogen production was also investigated. Sustained hydrogen production was carried out under natural, outdoor conditions as well. For the outdoor experiments, the highest hydrogen productivity and yield were obtained as 0.87 ± 0.06 mmol H₂ L^?1 h^?1 and 6.1 ± 0.2 mol H₂/mol sucrose, respectively on 10 mM sucrose. Furthermore, this system prevented sudden pH drops and fluctuations caused by the utilization of sucrose throughout the process. These results demonstrate that a proper immobilization setup can lead to long-term efficient and robust hydrogen production even under naturally varying conditions.     

Computational and experimental study of high-speed impact of metallic Taylor cylinders

High-speed impact of metallic Taylor cylinders is investigated computationally and experimentally. On the computational side, a modular explicit finite element hydrocode based on updated Lagrangian formulation is developed. A non-classical contour integration is employed to calculate the nodal forces in the constant strain axisymmetric triangular elements. Cell and nodal averaging of volumetric strain formulations are implemented on different mesh architectures to reduce the incompressibility constraints and eliminate volumetric locking. On the experimental side, a gas gun is designed and manufactured, and Taylor impact tests of cylinders made of several metallic materials are performed. Computational predictions of the deformed profiles of Taylor cylinders and experimentally determined deformed profiles are compared for verification purposes and to infer conclusions on the effect of yield strength, strain hardening and strain rate on the material response. The article also compares the performance of different plastic flow stress models that are incorporated into the hydrocode with the experimental results and results provided by previously reported simulations and tests.     

Use of consistency index, expert prioritization and direct numerical inputs for generic fuzzy-AHP modeling: A process model for shipping asset management

The aim of this paper is to develop a generic version of the conventional fuzzy-analytic hierarchy process (FAHP) method and investigate the shipping asset management (SAM) problem in the dry bulk shipping market. The recent literature has various applications of the FAHP, but these studies lack consistency control, use identical decision support rather than weighted expert choices, and lack measurable criteria. The proposed model, generic fuzzy-AHP (here after GF-AHP), provides a standard control of consistency on the decision matrix for the expert group. GF-AHP also improves the capabilities of the FAHP by executing direct numerical inputs without expert consultation. In practical business, some of the criteria can be easily calculated and expert consultation is a redundant process. Therefore, GF-AHP presents how to transform such numerical inputs to a priority scale. Finally, expertise differences on the decision group are reflected in the GF-AHP process by an expert weighting algorithm.     

A two-stage bid-price control for make-to-order revenue management

Capacity control implementations in make-to-order (MTO) revenue management typically are based on bid-prices, which are used to approximate the opportunity cost of accepting a customer request. However, in the face of stochastic demand, this approximation becomes less accurate and the performance of bid-prices may deteriorate. To address this problem, we examine the informational dynamics inherent in MTO capacity control problems and propose a two-stage capacity control approach based on bid-price updates. Updating is realized with neural networks, which are applied to adjust the selection criteria during the booking period with respect to online demand information. Not only is the resulting contribution margin positively influenced by the update, but also the downside risk of performing worse than a naive first-come-first-served policy. Results from computational experiments show that the proposed approach dominates traditional revenue management methods like randomized linear programming with and without resolving in expected contribution margin as well as in risk.     

Mechanical characterization of nickel nanowires by using a customized atomic force microscope

A new experimental method to characterize the mechanical properties of metallic nanowires is introduced. An accurate and fast mechanical characterization of nanowires requires simultaneous imaging and testing of the nanowires. However, existing mechanical characterization techniques fail to accomplish this goal due either to the lack of imaging capability of the mechanical test setup or the difficulty of individual alignment and manipulation of single nanowires for each test. In this study, nanowire specimens prepared by an electroplating technique are located on a silicon substrate with trenches. A customized atomic force microscope is located inside a scanning electron microscope (SEM) in order to establish the visibility of the nanowires, and the tip of the atomic force microscope cantilever is utilized to bend and break the nanowires. The ability to visualize the nanowires in an SEM improves the speed and accuracy of the tests. Experimentally obtained force versus bending displacement curves are fitted into existing analytical formulations to extract the mechanical properties. Experimental results reveal that nickel nanowires have significantly higher strengths than their bulk counterparts, although their elastic modulus values are comparable to bulk nickel modulus values.