Search results for: Gaussian process classification model with multiclass

Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

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Samarium as a rare-earth element is playing a growing important role in high technology. Traditional methods for extraction of rare earth metals such as ion exchange and solvent extraction have disadvantages of high investment and high energy consumption. Emulsion liquid membrane (ELM) as an improved solvent extraction technique is an effective transport method for separation of various compounds from aqueous solutions. In this work, the extraction of samarium from aqueous solutions by ELM was investigated using response surface methodology (RSM). The organic membrane phase of the ELM was a nanofluid consisted of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as mobile carrier, and kerosene as base fluid. 1 M nitric acid solution was used as internal aqueous phase. The effects of the important process parameters on samarium extraction were investigated, and the values of these parameters were optimized using the Central Composition Design (CCD) of RSM. These parameters were the concentration of MWCNT in nanofluid, the carrier concentration, and the volume ratio of organic membrane phase to internal phase (Roi). The three-dimensional (3D) response surfaces of samarium extraction efficiency were obtained to visualize the individual and interactive effects of the process variables. A regression model for % extraction was developed, and its adequacy was evaluated. The result shows that % extraction improves by using MWCNT nanofluid in organic membrane phase and extraction efficiency of 98.92% can be achieved under the optimum conditions. In addition, demulsification was successfully performed and the recycled membrane phase was proved to be effective in the optimum condition.

Keywords: Cyanex 272, emulsion liquid membrane, multiwalled carbon nanotubes, nanofluid, response surface methodology, Samarium.

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Authors: Ali Keshavarzi, Fereydoon Sarmadian

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Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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Authors: Leehter Yao, Chin-Chin Lin

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A novel method of learning complex fuzzy decision regions in the n-dimensional feature space is proposed. Through the fuzzy decision regions, a given pattern's class membership value of every class is determined instead of the conventional crisp class the pattern belongs to. The n-dimensional fuzzy decision region is approximated by union of hyperellipsoids. By explicitly parameterizing these hyperellipsoids, the decision regions are determined by estimating the parameters of each hyperellipsoid.Genetic Algorithm is applied to estimate the parameters of each region component. With the global optimization ability of GA, the learned decision region can be arbitrarily complex.

Keywords: Ellipsoid, genetic algorithm, decision regions, classification.

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Authors: G. Reinhart, S. Schindler

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Due to dynamic evolution, the ability of a manufacturing technology to produce a special product is changing. Therefore, it is essential to monitor the established techniques and processes to detect whether a company-s production will fit future circumstances. Concerning the manufacturing technology planning process, companies must decide when to change to a new technology for maintaining and increasing competitive advantages. In this context, the maturity assessment of the focused technologies is crucial. This article presents an approach for defining the maturity of a manufacturing technology from a strategic point of view. The concept is based on the approach of technology readiness level (TRL) according to NASA (National Aeronautics and Space Administration), but also includes dynamic changes. Therefore, the model takes into account the concept of the technology life cycle. Furthermore, it enables a company to estimate the ideal date for implementation of a new manufacturing technology.

Keywords: Maturity Assessment, Manufacturing Technology Planning, Technology Life Cycle, Technology Readiness Level.

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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Authors: Jayaletchumi T. Sambantha Moorthy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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Most quality models have defined usability as a significant factor that leads to improving product acceptability, increasing user satisfaction, improving product reliability, and also financially benefitting companies. Usability is also the best factor that balances both the technical and human aspects of a software product, which is an important aspect in defining quality during software development process. A usability risk consist risk factors that could impact the usability of a software product thereby contributing to negative user experiences and causing a possible software product failure. Hence, it is important to mitigate and reduce usability risks in the software development process itself. By managing possible usability risks in software development process, failure of software product could be reduced. Therefore, this research uses the Delphi method to identify mitigation plans for reducing potential usability risks. The Delphi method is conducted with seven experts from the field of risk management and software development.

Keywords: Usability, Usability Risk, Risk Management, Risk Mitigation, Delphi Method.

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Authors: Gesine Hellwig

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Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Keywords: Functional imaging, Tracer kinetic modeling, LTIsystem, Indicator dilution theory / convolution approach, Two-Compartment model.

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Authors: Catherine A. Todd, Fazel Naghdy

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In this work a surgical simulator is produced which enables a training otologist to conduct a virtual, real-time prosthetic insertion. The simulator provides the Ear, Nose and Throat surgeon with real-time visual and haptic responses during virtual cochlear implantation into a 3D model of the human Scala Tympani (ST). The parametric model is derived from measured data as published in the literature and accounts for human morphological variance, such as differences in cochlear shape, enabling patient-specific pre- operative assessment. Haptic modeling techniques use real physical data and insertion force measurements, to develop a force model which mimics the physical behavior of an implant as it collides with the ST walls during an insertion. Output force profiles are acquired from the insertion studies conducted in the work, to validate the haptic model. The simulator provides the user with real-time, quantitative insertion force information and associated electrode position as user inserts the virtual implant into the ST model. The information provided by this study may also be of use to implant manufacturers for design enhancements as well as for training specialists in optimal force administration, using the simulator. The paper reports on the methods for anatomical modeling and haptic algorithm development, with focus on simulator design, development, optimization and validation. The techniques may be transferrable to other medical applications that involve prosthetic device insertions where user vision is obstructed.

Keywords: Haptic modeling, medical device insertion, real-time visualization of prosthetic implantation, surgical simulation.

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Authors: O. P. Misra, Preety Kalra

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It is well recognized that the green house gases such as Chlorofluoro Carbon (CFC), CH4, CO2 etc. are responsible directly or indirectly for the increase in the average global temperature of the Earth. The presence of CFC is responsible for the depletion of ozone concentration in the atmosphere due to which the heat accompanied with the sun rays are less absorbed causing increase in the atmospheric temperature of the Earth. The gases like CH4 and CO2 are also responsible for the increase in the atmospheric temperature. The increase in the temperature level directly or indirectly affects the dynamics of interacting species systems. Therefore, in this paper a mathematical model is proposed and analysed using stability theory to asses the effects of increasing temperature due to greenhouse gases on the survival or extinction of populations in a prey-predator system. A threshold value in terms of a stress parameter is obtained which determines the extinction or existence of populations in the underlying system.

Keywords: Equilibria, Green house gases, Model, Populations, Stability.

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Authors: N. Khomarloo, F. Mousazadegan, M. Latifi, N. Hemmatinejad

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Recently, the utilization of reusable surgical gowns in order to decrease costs, environmental protection and enhance surgeon’s comfort is considered. One of the concerns in applying this kind of medical protective clothing is reduction of their resistance to bacterial penetration especially in wet state, after repeated laundering and sterilizing process. The purpose of this study is to investigate the effect of the laundering and sterilizing process on the reusable surgical gown’s resistance against bacterial wet penetration. To this end, penetration of Staphylococcus aureus bacteria in wet state after 70 washing and sterilizing cycles was evaluated on the two single-layer and three-layer reusable gowns. The outcomes reveal that up to 20 laundering and sterilizing cycles, protective property of samples improves due to fabric shrinkage, after that because of the fabric’s construction opening, the bacterial penetration increase. However, the three-layer gown presents higher protective performance comparing to the single-layer one.

Keywords: Reusable surgical gown, laundry, sterilization, wet bacterial penetration.

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Authors: Abhijit Mitra, C. Ardil

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We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.

Keywords: Auditory localization, Binaural sound, Head related impulse response, Head related transfer function, Interaural level difference, Interaural time difference, Localization cues.

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Authors: Mohammad Rajabalinejad

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Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: Safety, safety cube, design, product, system, machinery.

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Authors: Keisuke Nakamura, Kiyoshi Akama, Hiroshi Mabuchi

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E-Learning systems are used by many learners and teachers. The developer is developing the e-Learning system. However, the developer cannot do system construction to satisfy all of users- demands. We discuss a method of constructing e-Learning systems where learners and teachers can design, try to use, and share extending system functions that they want to use; which may be nally added to the system by system managers.

Keywords: Clause-Rule-Model, database-access, e-Learning, Web-Application.

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Authors: K. Sreelakshmi, P. Ramakanthkumar

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Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.

Keywords: Short term wind speed prediction, Neural networks, Back propagation.

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Authors: B. A. Gobin, R. K. Subramanian

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This paper gives an overview of how an OWL ontology has been created to represent template knowledge models defined in CML that are provided by CommonKADS. CommonKADS is a mature knowledge engineering methodology which proposes the use of template knowledge model for knowledge modelling. The aim of developing this ontology is to present the template knowledge model in a knowledge representation language that can be easily understood and shared in the knowledge engineering community. Hence OWL is used as it has become a standard for ontology and also it already has user friendly tools for viewing and editing.

Keywords: Ontology, OWL, Template Knowledge Models, CommonKADS

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Authors: Mounir Sayadi, Farhat Fnaiech

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In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.

Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari

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This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.

Keywords: Higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis.

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Authors: Fatma Ghangir, Andrzej F. Nowakowski, Franck C. G. A. Nicolleau, Thomas M. Michelitsch

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The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis.

Keywords: Multiphase flow, gas-liquid flow, Godunov schems, Riemann solvers, HLL scheme, HLLC scheme.

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Authors: Christian Castro Samaniego, Daniel Icaza Alvarez, Juan Portoviejo Brito

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For this research work, hybrid wind-photovoltaic (SHEF) systems were considered as renewable energy sources that take advantage of wind energy and solar radiation to transform into electrical energy. In the present research work, the feasibility of a wind-photovoltaic hybrid generation system was analyzed for the La Tranca tourist viewpoint of the Chordeleg canton in Ecuador. The research process consisted of the collection of data on solar radiation, temperature, wind speed among others by means of a meteorological station. Simulations were carried out in MATLAB/Simulink based on a mathematical model. In the end, we compared the theoretical radiation-power curves and the measurements made at the site.

Keywords: Hybrid system, wind turbine, modeling, simulation, validation, experimental data, panel, Ecuador.

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Authors: Manish K Rathod, Jyotirmay Banerjee

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The storage of thermal energy as a latent heat of phase change material (PCM) has created considerable interest among researchers in recent times. Here, an attempt is made to carry out numerical investigations to analyze the performance of latent heat storage units (LHSU) employing phase change material. The mathematical model developed is based on an enthalpy formulation. Freezing time of PCM packed in three different shaped containers viz. rectangular, cylindrical and cylindrical shell is compared. The model is validated with the results available in the literature. Results show that for the same mass of PCM and surface area of heat transfer, cylindrical shell container takes the least time for freezing the PCM and this geometric effect is more pronounced with an increase in the thickness of the shell than that of length of the shell.

Keywords: Enthalpy Formulation, Latent heat storage unit(LHSU), Numerical Model, Phase change material (PCM)

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Authors: Gulshan Sachdeva, Vaibhav Jain, S. S. Kachhwaha

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Cascade refrigeration systems employ series of single stage vapor compression units which are thermally coupled with evaporator/condenser cascades. Different refrigerants are used in each of the circuit depending on the optimum characteristics shown by the refrigerant for a particular application. In the present research study, a steady state thermodynamic model is developed which simulates the working of an actual cascade system. The model provides COP and all other system parameters e.g. total compressor work, temperature, pressure, enthalpy and entropy at different state points. The working fluid in low temperature circuit (LTC) is CO₂ (R744) while Ammonia (R717), Propane (R290), Propylene (R1270), R404A and R12 are the refrigerants in high temperature circuit (HTC). The performance curves of Ammonia, Propane, Propylene, and R404A are compared with R12 to find its nearest substitute. Results show that Ammonia is the best substitute of R12.

Keywords: Cascade system, Refrigerants, Thermodynamic model.

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM2.5, fugitive, emission inventory.

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Authors: M. Sadique, S. Ainane, Y. F. Yap, P. Rostron, E. Al Hajri

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The presence of sand in production lines in the oil and gas industries causes material degradation due to erosion-corrosion. The material degradation caused by erosion-corrosion in pipelines can result in a high cost of monitoring and maintenance and in major accidents. The process of erosion-corrosion consists of erosion, corrosion, and their interactions. Investigating and understanding how the erosion-corrosion process affects the degradation process in certain materials will allow for a reduction in economic loss and help prevent accidents. In this study, material loss due to erosion-corrosion of mild steel under impingement of sand-laden water at 90˚ impingement angle is investigated using a submerged impingement jet (SIJ) test. In particular, effects of jet velocity and sand loading on TWL due to erosion-corrosion, weight loss due to pure erosion and erosion-corrosion interactions, at a temperature of 29-33 °C in sea water environment (3.5% NaCl), are analyzed. The results show that the velocity and sand loading have a great influence on the removal of materials, and erosion is more dominant under all conditions studied. Changes in the surface characteristics of the specimen after impingement test are also discussed.

Keywords: Erosion-corrosion, flow velocity, jet impingement, sand loading.

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Authors: Raed H. Allawi

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Fracture pressure is the main parameter applied in wells design and used to avoid drilling problems like lost circulation. Thus, this study aims to predict the fracture pressure of oil reservoirs in the southern Iraq Oilfield. The data required to implement this study included bulk density, compression wave velocity, gamma-ray, and leak-off test. In addition, this model is based on the pore pressure which is measured based on the Modular Formation Dynamics Tester (MDT). Many measured values of pore pressure were used to validate the accurate model. Using sonic velocity approaches, the mean absolute percentage error (MAPE) was about 4%. The fracture pressure results were consistent with the measurement data, actual drilling report, and events. The model's results will be a guide for successful drilling in future wells in the same oilfield.

Keywords: Pore pressure, fracture pressure, overburden pressure, effective stress, drilling events.

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Authors: Chen Wu, Youquan Xu, Dandan Li, Ronghua Yang, Lijuan Wang

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In rough set models, tolerance relation, similarity relation and limited tolerance relation solve different situation problems for incomplete information systems in which there exists a phenomenon of missing value. If two objects have the same few known attributes and more unknown attributes, they cannot distinguish them well. In order to solve this problem, we presented two improved limited and variable precision rough set models. One is symmetric, the other one is non-symmetric. They all use more stringent condition to separate two small probability equivalent objects into different classes. The two models are needed to engage further study in detail. In the present paper, we newly form object classes with a different respect comparing to the first suggested model. We overcome disadvantages of non-symmetry regarding to the second suggested model. We discuss relationships between or among several models and also make rule generation. The obtained results by applying the second model are more accurate and reasonable.

Keywords: Incomplete information system, rough set, symmetry, variable precision.

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Authors: M. P. Chakravarthy, N. Ramanaiah, B. S. K.Sundara Siva Rao

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Taguchi approach was applied to determine the most influential control factors which will yield better tensile strength of the joints of pulse TIG welded 70/30 Cu-Ni alloy. In order to evaluate the effect of process parameters such as pulse frequency, peak current, base current and welding speed on tensile strength of Pulsed current TIG welded 70/30 Cu-Ni alloy of 5 mm thickness, Taguchi parametric design and optimization approach was used. Through the Taguchi parametric design approach, the optimum levels of process parameters were determined at 95% confidence level. The results indicate that the Pulse frequency, peak current, welding speed and base current are the significant parameters in deciding the tensile strength of the joint. The predicted optimal values of tensile strength of Pulsed current Gas tungsten arc welding (PC GTAW) of 70/30 Cu-Ni alloy welds are 368.8MPa.

Keywords: 70/30 Cu-Ni alloy, pulsed current GTAW, mechanical properties, Taguchi technique, analysis of variance.

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Authors: Wichai Pattanapol, Sarah J. Wakes, Michael J. Hilton, Katharine J.M. Dickinson

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Turbulence modeling of large-scale flow over a vegetated surface is complex. Such problems involve large scale computational domains, while the characteristics of flow near the surface are also involved. In modeling large scale flow, surface roughness including vegetation is generally taken into account by mean of roughness parameters in the modified law of the wall. However, the turbulence structure within the canopy region cannot be captured with this method, another method which applies source/sink terms to model plant drag can be used. These models have been developed and tested intensively but with a simple surface geometry. This paper aims to compare the use of roughness parameter, and additional source/sink terms in modeling the effect of plant drag on wind flow over a complex vegetated surface. The RNG k-ε turbulence model with the non-equilibrium wall function was tested with both cases. In addition, the k-ω turbulence model, which is claimed to be computationally stable, was also investigated with the source/sink terms. All numerical results were compared to the experimental results obtained at the study site Mason Bay, Stewart Island, New Zealand. In the near-surface region, it is found that the results obtained by using the source/sink term are more accurate than those using roughness parameters. The k-ω turbulence model with source/sink term is more appropriate as it is more accurate and more computationally stable than the RNG k-ε turbulence model. At higher region, there is no significant difference amongst the results obtained from all simulations.

Keywords: CFD, canopy flow, surface roughness, turbulence models.

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Authors: S. N. Hosseini, M. H. Enayati, F. Karimzadeh, N. M. Sammes

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The synthesis of CuFe2O4 spinel powders by an optimized combustion-like process followed by calcination is described herein. The samples were characterized using X-ray diffraction (XRD), differential thermal analysis (TG/DTA), scanning electron microscopy (SEM), dilatometry and 4-probe DC methods. Different glycine to nitrate (G/N) ratios of 1 (fuel-deficient), 1.48 (stoichiometric) and 2 (fuel-rich) were employed. Calcining the asprepared powders at 800 and 1000°C for 5 hours showed that the G/N ratio of 2 results in the formation of the desired copper spinel single phase at both calcination temperatures. For G/N=1, formation of CuFe2O4 takes place in three steps. First, iron and copper nitrates decompose to iron oxide and pure copper. Then, copper transforms to copper oxide and finally, copper and iron oxides react with each other to form a copper ferrite spinel phase. The electrical conductivity and the coefficient of thermal expansion of the sintered pelletized samples were 2 S.cm-1 (800°C) and 11×10-6 °C-1 (25-800°C), respectively.

Keywords: SOFC interconnect coatings, Copper ferrite, Spinels, Electrical conductivity, Glycine–nitrate process.

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Authors: András Szekrényes

Abstract:

Delamination is one of the major failure modes in laminated composite structures. Delamination tips are mostly captured by spatial numerical models in order to predict crack growth. This paper presents some mechanical models of delaminated composite shells based on shallow shell theories. The mechanical fields are based on a third-order displacement field in terms of the through-thickness coordinate of the laminated shell. The undelaminated and delaminated parts are captured by separate models and the continuity and boundary conditions are also formulated in a general way providing a large size boundary value problem. The system of differential equations is solved by the state space method for an elliptic delaminated shell having simply supported edges. The comparison of the proposed and a numerical model indicates that the primary indicator of the model is the deflection, the secondary is the widthwise distribution of the energy release rate. The model is promising and suitable to determine accurately the J-integral distribution along the delamination front. Based on the proposed model it is also possible to develop finite elements which are able to replace the computationally expensive spatial models of delaminated structures.

Keywords: J-integral, Lévy method, third-order shell theory, state space solution.

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Authors: Pilar Rey-del-Castillo, Jesús Cardeñosa

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There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson-s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.

Keywords: Classifier, imputation techniques, fuzzy systems, fuzzy min-max neural networks.

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