Artificial Pinning Centers on MgB2 Superconducting Thin Films Coated by FeO Nanoparticles

MgB₂ thin films were fabricated on MgO (100) single crystal substrates. First, deposition of boron was performed by rf magnetron sputtering on MgO substrates and followed by a post deposition annealing at 850?°C in magnesium vapor. In order to investigate the effect of FeO nanoparticles on magnetic properties of MgB₂ thin films, the films were coated with different concentrations of FeO nanoparticles by spin coating process. The magnetic field dependence of the critical current density $J_{\mathrm{c}}$ was calculated from the M?CH loops and also magnetic field dependence of the pinning force density $f_{\mathrm{p}}(b)$ was determined for the films containing different concentrations of FeO nanoparticles. The values of the critical current density $J_{\mathrm{c}}$ in zero field at 5?K was found to be around 1×10⁶?A/cm² for pure MgB₂ film, 1.4×10⁶ for MgB₂ film coated with 25?%, 7.2×10⁵ for MgB₂ film coated with 33?%, 9.1×10⁵ for MgB₂ film coated with 50?% and 1.1×10⁶?A/cm² for MgB₂ film coated with 100?%. It?was?found that the film coated with 25?% FeO nanoparticles has slightly enhanced critical current density and it can be noted that especially the film coated with 25?% FeO became stronger in the magnetic field. The films coated with FeO were successfully produced and they indicated the presence of artificial pinning centers created by FeO nanoparticles. The superconducting transition temperature of the film coated with 25?% FeO nanoparticles was determined by moment?Ctemperature (M?CT) measurement to be 34?K which is 4?K higher than that of the pure film.     

Estimation of plastic deformation and abrasive wear in warm forging dies

In warm forging, die life is affected by abrasive wear and plastic deformation and may be shortened considerably due to thermal softening of the die surface caused by forging temperature and pressure. In this study, a methodology is developed for estimating abrasive die wear and plastic deformation in a warm forging operation, using a tempering parameter. This methodology consists of: (a) determination of the steady state die temperatures using multiple FE simulations, (b) using the calculated temperatures to predict the plastic deformation of the dies, (c) measuring the surface profile of the worn dies using a Coordinate Measuring Machine (CMM), (d) identifying the wear profiles caused by abrasive wear and plastic deformation, and (e) determining the abrasive wear parameters that can be used for future estimation of die wear in warm forging. The predictions have been compared with experimental results and it was concluded that this method can be used for estimation of die failure (wear and plastic deformation) in hot/warm forging.     

A hybrid methodology of fuzzy grey relation for determining multi attribute customer preferences of edible oil

The main idea behind this study is to introduce a fuzzy grey relational methodology (FGRM) to determine the importance of customer attributes’ (CAs) for edible oil, particularly for defining the opportunity of competitiveness which has recently become one of an important concern of manufacturing companies. It was also aimed to seek high quality level of product and process characteristics for meeting the desirability of attributes and for health care. A fuzzy grey inference system was employed with the support of fuzzy quality function (QFD) deployment to interpret the qualitative and imprecise customer attributes. Fuzzy QFD is relatively a recent methodology offering a more in-depth analysis and investigation into the handling of customer requirements and engineering characteristics. The attributes then were defuzzified into quantitative values by amalgamating the knowledge of the customers and the product designers.Customer needs (CNs) are the voice of customers and tend to be linguistic naturally. In this study, fuzzy inference system (FIS) along with fuzzy QFD was employed to determine the desirability of edible oil by consumers. Fuzzy QFD is a powerful tool for improving product design and quality, and procuring a customer-driven quality system. The integrated framework based on FIS, fuzzy QFD and FGRM determined the CAs relations, and desirability level of edible oil by consumers. The findings are not only meaningful for customers, but also important for market position of product. The methodology significantly reduces the complexity of decision making and increase the production efficiency and overall competitiveness.     

Signature verification (SV) toolbox: Application of PSO-NN

Analysis of signature is a widely used and developed area of research for personal verification. A typical signature verification (SV) system generally consists of four components: data acquisition, pre-processing, feature extraction and verification. A reliable SV toolbox, based on the verification of off-line signatures is developed with the proposed algorithm. The technique is based on a neural network (NN) approach trained with particle swarm optimization (PSO) algorithm. To test the performance of the proposed PSO-NN algorithm two types of forgeries—unskilled and skilled—are examined. The experimental results are illustrated on the selected signature databases and presented herein.     

Issues in convergence improvement for non-linear finite element programs

Systems of non-linear equations as they arise when analysing various physical phenomena and technological processes by the implicit Finite Element Method (FEM) are commonly solved by the Newton–Raphson method. The modelling of sheet metal forming processes is one example of highly non-linear problems where the iterative solution procedure can become very slow or diverge. This paper focuses on techniques to overcome these numerical difficulties. Several methods to generate initial guesses within the radius of convergence are proposed. Appropriate stopping criteria for the iterative procedure are discussed. A combination of various line search methods with the continuation method is proposed. The efficiency and robustness of these numerical procedures are compared based on a set of test examples. A particular form of line search was identified which allows the stable and efficient solution of highly non-linear sheet metal forming problems. Even though the present investigations were motivated by the application of the implicit FEM to the simulation of sheet metal forming processes, the findings are general enough to be applicable to a wide spectrum of non-linear FEM applications. © 1997 John Wiley & Sons, Ltd.     

Evaluation of tubular materials by a hydraulic bulge test

This paper aims to evaluate the properties of tubular materials by hydraulic bulge tests combined with a newly proposed analytical model. Annealed AA6011 aluminum tubes and SUS409 stainless steel tubes are used for the bulge test. The tube thickness at the pole, bulge height and the internal forming pressure are measured simultaneously during the bulge test. From above experimental data, the effective stress–effective strain relations can be derived by this analytical model assuming the profile of the free bulge region as an elliptical surface. The flow stresses of the tubular materials by this approach are compared with those obtained by the tensile test and Fuchizawa's model. The finite element method is used to conduct the simulations of hydraulic bulge forming with the flow stresses obtained by the above-mentioned models. The analytical results of forming pressures versus bulge heights are compared with the experimental results to validate the approach proposed in this paper.     

Evaluation of stamping lubricants using the deep drawing test

This paper presents a practical methodology that uses the deep drawing test and finite element (FE) analysis to evaluate stamping lubricants under near production conditions. In stamping operations good lubrication helps to reduce wrinkling, premature fracture, and localized thinning. Furthermore, lubrication also reduces tool wear in large-volume production. Determination of reliable friction data associated with a given lubrication system is also important for successful process design and simulation by FE analysis. In this study, five stamping lubricants (four dry film lubes and one wet lube) were evaluated using the deep drawing test. The performance of the lubricants were evaluated based on: (a) maximum punch force measured, (b) the maximum applicable blank holder force (BHF), (c) the draw-in length, (d) the perimeter of flange after test, (e) the change of surface roughness, and (f) the inspection of surface topography. The coefficient of friction for each lubricant tested was determined through the FE-based inverse analysis by matching the predicted and measured values of the load-stroke curve and the draw-in length. This study showed that one of the tested lubricants was most effective, regardless of test speed and the magnitude of BHF. The methodology used was shown to be effective in evaluating various lubricants for sheet metal forming and accurately differentiating their performances.     

Evaluation of new cold forging lubricants without zinc phosphate precoat

Zinc phosphate coatings plus metal soap lubrication system is required in nearly all steel cold forging operations. However, the chemical byproducts of this lubricant system are difficult to dispose of and have a negative environmental impact. In order to replace zinc phosphate based lubricants partially or completely, candidate lubricants were sought from lubricant manufacturers worldwide. The performance evaluation of these lubricants was conducted using the double cup backward extrusion test developed at the Engineering Research Center for Net Shape Manufacturing (ERC/NSM). With the use of the commercial FEM code DEFORM, friction factor calibration curves, i.e. cup height ratio vs. punch stroke, were established for different friction factor values. By matching the cup height ratio and the punch stroke from experiment to that obtained from FE simulations, the friction factor of the lubricants was determined. Three lubricants; namely, MEC Homat, Daido AquaLub, and MCI Z-Coat, were found to perform comparable to or better than zinc phosphate.     

Thermorheological properties of asphalt binders

The rheological properties of different types of asphalt binders were studied and compared considering their constituents and physical characteristics. The saturate, aromatic, resin, and asphaltene (SARA) analysis and differential scanning calorimetry (DSC) have shown their individual constituents and two distinct glass transition temperatures, indicating the phase changes of the two main components of the asphalt binders, namely asphaltenes and maltenes. Rheological characterization was performed over a wide range of temperatures (−10°C-60°C) showing that these materials may exhibit viscoelastic solid to viscous liquid behaviour. Master curves of complex viscosity, storage modulus, and loss modulus were constructed by applying the time-temperature superposition principle, which was found applicable over the temperature range considered. Stress relaxation and steady-shear test were applied to the samples in order to determine their rheological behaviour in the nonlinear viscoelastic regime (viscosity and nonlinear relaxation modulus). The rheological results were modelled and revealed that the Kaye-Bernstein-Kearsley-Zappas (K-BKZ) constitutive equation is suitable in representing the rheological behaviour of asphalts. The SARA analysis and rheological measurements were found to be compatible.     

Estimating Evaporation Using ANFIS

Water resources engineering assessment requires simple but effective evaporation estimation procedures, especially from readily measurable meteorological factors. Unfortunately, such approaches are rather scarce in the literature. In this paper, an adaptive neural-based fuzzy inference system (ANFIS) was applied to daily meteorology data from the Lake E?irdir region in the southwestern part of Turkey. Daily evaporation, solar radiation, air and water temperatures, and relative humidity measurements were used to develop the ANFIS method, which helps to assess possible contributions that each input variable has on the evaporation estimates. Such an assessment is not possible by any conventional procedure including the Penman method. However, the Penman method daily evaporation estimations were used as output data for the verification of the ANFIS approach. Classical evaporation estimation models treat the data individually. However, ANFIS models process past data collectively and then adaptively provide estimates as new sets of data become available. In the ANFIS architecture as developed in this paper, there are four measured input variables and one output variable to estimate evaporation. The estimation results from the ANFIS model had a high coefficient of determination of 0.98 when compared with the Penman method results and a low average performance error of 4.6% among other alternatives. The average performance error is less than the practically acceptable limit of 10%.