Prioritization methodology of dangerous substances for water quality monitoring with scarce data

Monitoring and control of dangerous substances discharged into receiving waters have attracted more attention lately. Since it is not possible to analyze every single substance, a prioritization methodology is needed for the selection of those to be monitored. Existing well-developed models require significant amount of data for reliable outcomes. This paper presents a methodology to prioritize the dangerous substances having adverse effects on freshwaters in Turkey, where data are scarce. Such a methodology will also serve as a solid model for other countries with limited background data. The adopted methodology enabled the elimination of chemicals to generate a candidate list composed of 608 substances among more than 5000 substances. Further screening and prioritization were conducted using different assessment methods (i.e., Total Hazard Value, Total Impact Value, Combined Monitoring-based, and Modelling-based Priority Setting) to obtain a proposed Final Candidate Specific Pollutants List of 150 dangerous substances. The proposed Candidate National Pollutant List of Turkey was established by combining 45 priority pollutants of the European Union with a list of candidate specific pollutants. According to the outcomes of this study, monitoring and controlling of 195 dangerous substances in freshwaters are recommended. Further detailed studies should be conducted in order to observe the actual levels of these dangerous substances in freshwaters followed by a review of the monitoring list accordingly. Moreover, further revisions might be required in the proposed list due to some possible versatile conditions in terms of sampling points (i.e., change in the location of industries).     

Multi-dimensional clearing functions for aggregate capacity modelling in multi-stage production systems

Nonlinear clearing functions have been proposed in the literature as metamodels to represent the behaviour of production resources that can be embedded in optimisation models for production planning. However, most clearing functions tested to date use a single-state variable to represent aggregate system workload over all products, which performs poorly when product mix affects system throughput. Clearing functions using multiple-state variables have shown promise, but require significant computational effort to fit the functions and to solve the resulting optimisation models. This paper examines the impact of aggregation in state variables on solution time and quality in multi-item multi-stage production systems with differing degrees of manufacturing flexibility. We propose multi-dimensional clearing functions using alternative aggregations of state variables, and evaluate their performance in computational experiments. We find that at low utilisation, aggregation of state variables has little effect on system performance; multi-dimensional clearing functions outperform single-dimensional ones in general; and increasing manufacturing flexibility allows the use of aggregate clearing functions with little loss of solution quality.     

Influence of coronene addition on some superconducting properties of bulk MgB<Subscript>2</Subscript>

This study reports the effect of coronene (C₂₄H₁₂) addition on some superconducting properties such as critical temperature (T_c), critical current density (J_c), flux pinning force density (F_p), irreversibility field (H_irr), upper critical magnetic field (H_c2), and activation energy (U₀), of bulk MgB₂ superconductor by means of magnetisation and magnetoresistivity measurements. Disk-shaped polycrystalline MgB₂ samples with varying C₂₄H₁₂ contents of 0, 2, 4, 6, 8, 10 wt%, were produced at 850 °C in Ar atmosphere. The obtained results show an increase in field-J_c values at 10 and 20 K resulting from the strengthened flux pinning, and a decrease in critical temperature (T_c) because of C substitution into MgB₂ lattice, with increasing amount of C₂₄H₁₂ powder. The H_c2(0) and H_irr(0) values are respectively found as 144, 181, 172 kOe, and 128, 161, 145 kOe for pure, 4 wt% and 10 wt% C₂₄H₁₂ added samples. The U₀ depending on the magnetic field curves were plotted using thermally activated flux flow model. The maximum U₀ values are respectively obtained as 0.20, 0.23 and 0.12 eV at 30 kOe for pure, 4 wt% and 10 wt% C₂₄H₁₂ added samples. As a result, the superconducting properties of bulk MgB₂ at high fields was improved using C₂₄H₁₂, active carbon source addition, because of the presence of uniformly dispersed C particles with nanometer order of magnitude, and acting as effective pinning centres in MgB₂ structure.     

Leaching behavior of pollutants in ferrochrome arc furnace dust and its stabilization/solidification using ferrous sulphate and Portland cement

In this study, dissolution properties under different conditions and pollution potential by toxicity characteristic leaching procedure (TCLP) of arc furnace dust generated in the production of ferrochrome were examined and some stabilization/solidification (S/S) techniques were applied to the dust depending on contaminants determined. Dissolution properties and pollution potentials of all the materials stabilized/solidified were also studied under the similar conditions. It was determined that the metallic components concentrations dissolved from the ferrochrome arc furnace dust (FAFD) except for chromium and zinc were below the detection limits. The chromium concentration dissolved from the FAFD by TCLP was found to be 9.8 mg/l. Portland cement (PC), PC-FeSO(4) and PC-sand-FeSO(4) mixtures for S/S of the FAFD were tested. Although metal ions in the cationic form were stabilized when the PC was only used, Cr(VI) in the sample was not changed depending on PC amount and remained in the soluble chromate form. The stabilization efficiency of Cr(VI) increased by the increasing amounts of PC and FeSO(4). The best S/S of the FAFD was accomplished when the 5 stoichiometric amounts of FeSO(4), 30% PC and 16% sand mixture were used. TCLP leaching results of the samples obtained under the optimum conditions were below the EPA landfilling limits.     

New current–mode special function continuous-time active filters employing only OTAs and OPAMPs

This paper reports three current mode second order filters, each of which realizes a specific function without any external passive elements. These filters realize low-pass notch (LPN), high-pass notch (HPN) and all-pass (AP) functions. Two OPAMPs, a double output OTA and a single output OTA are employed for each circuit. The filter structures can be easily cascaded since they have high output impedances. This property is especially useful for achieving high-order filters using these LPN and HPN filters as building blocks. The presented theory is verified with macro models in SPICE simulations and, using the SPICE parameters of the layout technology, post layout simulations are carried out, with parasitics extracted from the layouts of the filter chips.     

Dynamic modeling and fuzzy logic control of vibrations of a railway vehicle for different track irregularities

Safe and comfortable transportation of passengers and goods on railways can be achieved by solving the vibration problem. In this study, the dynamic modeling of the full railway vehicle is used to perform vibration analysis in order to observe displacements and accelerations. The full railway vehicle model consists of 54 degrees of freedom which are defined by differential equations. Additionally, wheel–rail contact problem (i.e. creepage factors and hertzian spring stiffness of rails) is analyzed by finite element method. Dynamic modeling and vibration analysis are carried out using Matlab–Simulink software. Using the developed model, the car body vibrations, caused by a lateral and two vertical sinusoidal track irregularities, are controlled by fuzzy logic controllers placed between the car body and bogies. The fuzzy logic algorithm herein is used for realizing the active control of car body vibrations. The simulations of vibration analysis are obtained in time and frequency domains and compared with passive controlled status. The robustness of the designed controller is verified by simulations, carried out for the cases of car body mass variations. The results show the effectiveness of the proposed algorithm.     

Effect of cathodic arc plasma treatment on the properties of WC–Co based hard metals

In this study, ion bombardment in a cathodic arc physical vapor deposition system was applied on WC–Co hard metal surfaces aiming to benefit from the diffusion acceleration effect, and to investigate the role of this effect on the surface composition, morphology and corrosion resistance of the materials. Chromium ions obtained via cathodic arc evaporation were accelerated under low (− 150 V) and high (− 1000 V) bias voltages in order to apply coating–bombardment cycles to sample surfaces. Substrate temperatures were measured by an optical pyrometer during the processes. The treated samples were characterized by scanning electron microscopy (SEM) and X-ray diffractometry (XRD). Temperature measurements showed that the sample temperature could be controlled precisely by adjusting the bias voltage. Temperatures in the range of 750–1200 °C were measured during the treatment depending on the duration of the high bias voltage cycles. XRD analysis showed η phase formation in the near surface regions of all treated samples. The amount of the formed η phase was shown to be dependent on the heating–cooling regime that varied with the applied mode of bias. The corrosion behavior of the samples was investigated by immersing treated and untreated samples in a solution of 5% H₃PO₄ containing 1 g/l Zn^{+ 2} for 24 h at 50 °C. The samples were investigated via SEM observations after immersion. Cathodic arc plasma treated samples showed a better resistance to corrosion in this environment.     

Various approaches for constructing an ensemble of metamodels using local measures

Metamodels are approximate mathematical models used as surrogates for computationally expensive simulations. Since metamodels are widely used in design space exploration and optimization, there is growing interest in developing techniques to enhance their accuracy. It has been shown that the accuracy of metamodel predictions can be increased by combining individual metamodels in the form of an ensemble. Several efforts were focused on determining the contribution (or weight factor) of a metamodel in the ensemble using global error measures. In addition, prediction variance is also used as a local error measure to determine the weight factors. This paper investigates the efficiency of using local error measures, and also presents the use of the pointwise cross validation error as a local error measure as an alternative to using prediction variance. The effectiveness of ensemble models are tested on several problems with varying dimensionality: five mathematical benchmark problems, two structural mechanics problems and an automobile crash problem. It is found that the spatial ensemble models show better performances than the global ensemble for the low-dimensional problems, while the global ensemble is a more accurate model than the spatial ensembles for the high-dimensional problems. Ensembles based on pointwise cross validation error and prediction variance provide similar accuracy. The ensemble models based on local measures reduce cross validation errors drastically, but their performances are not that impressive in reducing the error evaluated at random test points, because the pointwise cross validation error is not a good surrogate for the error at a point.     

Stills,not full motion,for interactive spatial training: American,Turkish and Taiwanese female pre-service teachers learn spatial visualization

This study investigated how female elementary education pre-service teachers in the United States, Turkey and Taiwan learned spatial skills from structured activities involving discrete, as opposed to continuous, transformations in interactive computer programs, and how these activities transferred to non-related standardized tests of spatial visualization and mental rotation. The study used a pretest, intervention, posttest research design with experimental and comparison groups. The experimental group participated in transformational geometry visualization exercises, once a week for six weeks, for approximately 20 minutes each session. Instruments were standardized measures of spatial visualization and mental rotation; intervention activity worksheets directed the participants through 2D and 3D transformational geometry tasks in computer environments. For Turkish and Taiwanese participants, the experimental group improved significantly more than the control group in spatial visualization, while the American participants showed no such significant improvement.     

Preparation of nano-size ZrB2 powder by self-propagating high-temperature synthesis

Preparation of nano-size ZrB₂ powder by SHS has been investigated. Zr and B elemental powders were mixed with 10–50 wt.% NaCl, and prepared pellets were reacted under argon. Adiabatic temperatures were calculated by HSC software. Increasing NaCl content led to a continuous decrease in adiabatic temperatures and reaction wave velocity. Products were subjected to XRD, SEM and FESEM analyses. Average crystallite size of ZrB₂, which was 303 nm without NaCl, decreased to 32 nm with 40% NaCl addition. Distinct decrease in ZrB₂ particle size was also observed from SEM analyses. 30% NaCl addition was found to be optimum for ensuring a stable SHS reaction and providing the formation of nano-size ZrB₂ particles. It was revealed from particle size distribution measurements that ZrB₂ powder obtained by 30 wt.% NaCl addition contained particles mostly finer than 200 nm. A mechanism, similar to solution-precipitation was proposed for the particle size refining effect of NaCl.