Search results for: function analysis system technique

Authors: Lalnuntluanga Hmar, Hardik Vyas

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Hydraulic fracturing has become an essential procedure to break apart the rock and release the oil or gas which are trapped tightly in the rock by pumping fracturing fluids at high pressure down into the well. To open the fracture and to transport propping agent along the fracture, proper selection of fracturing fluids is the most crucial components in fracturing operations. Rheology properties of the fluids are usually considered the most important. Among various fracturing fluids, Borate crosslinked fluids have proved to be highly effective. Borate in the form of Boric Acid, borate ion is the most commonly use to crosslink the hydrated polymers and to produce very viscous gels that can stable at high temperature. Guar and HPG (Hydroxypropyl Guar) polymers are the most often used in these fluids. Borate gel rheology is known to be a function of polymer concentration, borate ion concentration, pH, and temperature. The crosslinking using Borate is a function of pH which means it can be formed or reversed simply by altering the pH of the fluid system. The fluid system was prepared by mixing base polymer with water at pH ranging between 8 to 11 and the optimum borate crosslinker efficiency was found to be pH of about 10. The rheology of laboratory prepared Borate crosslinked fracturing fluid was determined using Anton Paar Rheometer and Fann Viscometer. The viscosity was measured at high temperature ranging from 200ᵒF to 250ᵒF and pressures in order to partially stimulate the downhole condition. Rheological measurements reported that the crosslinking increases the viscosity, elasticity and thus fluid capability to transport propping agent.

Keywords: borate, crosslinker, Guar, Hydroxypropyl Guar (HPG), rheology

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Authors: Salihah Alghamdi, Surajit Ray

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Space-time data can be observed over irregularly shaped manifolds, which might have complex boundaries or interior gaps. Most of the existing methods do not consider the shape of the data, and as a result, it is difficult to model irregularly shaped data accommodating the complex domain. We used a method that can deal with space-time data that are distributed over non-planner shaped regions. The method is based on partial differential equations and finite element analysis. The model can be estimated using a penalized least squares approach with a regularization term that controls the over-fitting. The model is regularized using two roughness penalties, which consider the spatial and temporal regularities separately. The integrated square of the second derivative of the basis function is used as temporal penalty. While the spatial penalty consists of the integrated square of Laplace operator, which is integrated exclusively over the domain of interest that is determined using finite element technique. In this paper, we applied a spatio-temporal regression model with partial differential equations regularization (ST-PDE) approach to analyze a remote sensing data measuring the greenness of vegetation, measure by an index called enhanced vegetation index (EVI). The EVI data consist of measurements that take values between -1 and 1 reflecting the level of greenness of some region over a period of time. We applied (ST-PDE) approach to irregular shaped region of the EVI data. The approach efficiently accommodates the irregular shaped regions taking into account the complex boundaries rather than smoothing across the boundaries. Furthermore, the approach succeeds in capturing the temporal variation in the data.

Keywords: irregularly shaped domain, partial differential equations, finite element analysis, complex boundray

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Authors: Hamsa T. Tayeb, Mohammad A. Arafah, Dana M. Bakheet, Duaa M. Khalaf, Agnieszka Tarnoska, Nduna Dzimiri

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Background: CYP2D6 is a member of the cytochrome P450 mixed-function oxidase system. The enzyme is responsible for the metabolism and elimination of approximately 25% of clinically used drugs, especially in breast cancer and psychiatric therapy. Different phenotypes have been described displaying alleles that lead to a complete loss of enzyme activity, reduced function (poor metabolizers – PM), hyperfunctionality (ultrarapid metabolizers–UM) and therefore drug intoxication or loss of drug effect. The prevalence of these variants may vary among different ethnic groups. Furthermore, the xTAG system has been developed to categorized all patients into different groups based on their CYP2D6 substrate metabolization. Aim of the study: To determine the prevalence of the different CYP2D6 variants in our population, and to evaluate their clinical relevance in personalized medicine. Methodology: We used the Luminex xMAP genotyping system to sequence 305 Saudi individuals visiting the Blood Bank of our Institution and determine which polymorphisms of CYP2D6 gene are prevalent in our region. Results: xTAG genotyping showed that 36.72% (112 out of 305 individuals) carried the CYP2D6_*2. Out of the 112 individuals with the *2 SNP, 6.23% had multiple copies of *2 SNP (19 individuals out of 305 individuals), resulting in an UM phenotype. About 33.44% carried the CYP2D6_*41, which leads to decreased activity of the CYP2D6 enzyme. 19.67% had the wild-type alleles and thus had normal enzyme function. Furthermore, 15.74% carried the CYP2D6_*4, which is the most common nonfunctional form of the CYP2D6 enzyme worldwide. 6.56% carried the CYP2D6_*17, resulting in decreased enzyme activity. Approximately 5.73% carried the CYP2D6_*10, consequently decreasing the enzyme activity, resulting in a PM phenotype. 2.30% carried the CYP2D6_*29, leading to decreased metabolic activity of the enzyme, and 2.30% carried the CYP2D6_*35, resulting in an UM phenotype, 1.64% had a whole-gene deletion CYP2D6_*5, thus resulting in the loss of CYP2D6 enzyme production, 0.66% carried the CYP2D6_*6 variant. One individual carried the CYP2D6_*3(B), producing an inactive form of the enzyme, which leads to decrease of enzyme activity, resulting in a PM phenotype. Finally, one individual carried the CYP2D6_*9, which decreases the enzyme activity. Conclusions: Our study demonstrates that different CYP2D6 variants are highly prevalent in ethnic Saudi Arabs. This finding sets a basis for informed genotyping for these variants in personalized medicine. The study also suggests that xTAG is an appropriate procedure for genotyping the CYP2D6 variants in personalized medicine.

Keywords: CYP2D6, hormonal breast cancer, pharmacogenetics, polymorphism, psychiatric treatment, Saudi population

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Authors: Chika Catherine Ayogu

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Rehabilitation plays an important and integral part in the life of roadway rehabilitation management system. It is a systematic method for inspection and rating the roadway condition in a given area. The system performs a cost effective analysis of various maintenance and rehabilitation strategies. Finally the system prioritize and recommend roadway rehabilitation and maintenance to maximize results within a given budget amount. During execution of maintenance activity, the system also tracks labour, materials, equipment and cost for activities performed. The system implements physical assessment field inspection and rating of each street segment which is then entered into a database. The information is analyzed using a software, and provide recommendations and project future conditions. The roadway management system provides a deterioration curve for each segment based on input then assigns the most cost-effective maintenance strategy based on conditions, surface type and functional classification, and available budget. This paper investigates the roadway management system and its capabilities to assist in applying the right treatment to the right roadway at the right time so that expected service life of the roadway is extended as long as possible with acceptable cost.

Keywords: effectiveness, rehabilitation, roadway, software system

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Authors: El Miloudi Djelloul

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Based on analysis on applications by perception control technology in computer network security status and security protection measures, from the angles of network physical environment and network software system environmental security, this paper provides network security system perception control solution using Internet of Things (IOT), telecom and other perception technologies. Security Perception Control System is in the computer network environment, utilizing Radio Frequency Identification (RFID) of IOT and telecom integration technology to carry out integration design for systems. In the network physical security environment, RFID temperature, humidity, gas and perception technologies are used to do surveillance on environmental data, dynamic perception technology is used for network system security environment, user-defined security parameters, security log are used for quick data analysis, extends control on I/O interface, by development of API and AT command, Computer Network Security Perception Control based on Internet and GSM/GPRS is achieved, which enables users to carry out interactive perception and control for network security environment by WEB, E-MAIL as well as PDA, mobile phone short message and Internet. In the system testing, through middle ware server, security information data perception in real time with deviation of 3-5% was achieved; it proves the feasibility of Computer Network Security Perception Control System.

Keywords: computer network, perception control system security strategy, Radio Frequency Identification (RFID)

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Authors: Byeong-Sam Kim, Kyoungwoo Park

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This research analyzes structure of flat panel display (FPD) such as LCD as quantitative through CFD analysis and modeling change to minimize the badness rate and rate of production decrease by damage of large scale plater at wafer heating chamber at semi-conductor manufacturing process. This glass panel and wafer device with atmospheric pressure or chemical vapor deposition equipment for transporting and transferring wafers, robot hands carry these longer and wider wafers can also be easily handled. As a contact handling system composed of several problems in increased potential for fracture or warping. A non-contact handling system is required to solve this problem. The panel and wafer warping makes it difficult to carry out conventional contact to analysis. We propose a new non-contact transportation system with combining air suction and blowout. The numerical analysis and experimental is, therefore, should be performed to obtain compared to results achieved with non-contact solutions. This wafer panel noncontact handler shows its strength in maintaining high cleanliness levels for semiconductor production processes.

Keywords: flat panel display, non contact transportation, heat treatment process, CFD analysis

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Authors: Abdul Haris Setiawan

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Teachers empowerment is one of the important factors considered to contribute significantly to the achievement of the national education goals. This study was conducted to determine the influence on the vocational teachers empowerment toward the performance of the vocational high schools based on the Education National Standards of Indonesia. The population of the study was all vocational teachers at the State Vocational High schools in Surakarta, Central Java Province, Indonesia. The sampling technique used proportional random sampling technique. This study used a quantitative descriptive statistical analysis techniques. The data was collected using questionnaires. The data has been collected and then tested using analysis requirements test. Having tested using the requirements analysis and then the data processed using regression analysis between the independent and dependent variables to determine the effect and the regression equation. The results of the study found that the level of vocational high schools’ performance based on the Education National Standards of Indonesia was 74.29%, including in the high category; the level of vocational teachers empowerment was 76.20%, including in the high category; there was a positive influence of vocational teachers empowerment toward the vocational high schools’ performance based on the Education National Standards of Indonesia with a correlation coefficient of 0,886, and a contribution of 78.50% with the regression equation Y = 79.431 +0.534 X.

Keywords: vocational teachers, empowerment, vocational high school, the education national standards

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Authors: Selva Georgena D., Videcoq Etienne, Caner Julien, Benselama Adel, Girault Manu

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A Two-Phase Thermosyphon Loop (TPTL) is a passive cooling system which does not require a pump to function. Therefore, TPTL is a simple and robust device and its physics is complex to describe because of the coupled phenomena: heat flux, nucleation, fluid dynamics and gravitational effects. Moreover, the dynamic behavior of TPTL shows some physical instabilities and the actual occurrence of such a behavior remains unknown. The aim of this study is to propose a thermal balance of the TPTL to better identify the fundamental reasons for the appearance of the instabilities.

Keywords: Two-phase flow, passive cooling system, thermal reliability, thermal experimental study, liquid-vapor phase change

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

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Authors: Yamin Sayyari

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In this paper, we generalized the Jensen's inequality for m-convex functions and also we present a correction of Jensen's inequality which is a better than the generalization of this inequality for m-convex functions. Finally, we have found new lower and new upper bounds for Jensen's discrete inequality.

Keywords: Jensen's inequality, m-convex function, Convex function, Inequality

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Authors: Arunas Burinskas, Manuela Tvaronavičienė

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Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

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Authors: Hanadi Mohamed Shawgi Gamal, Claus Thomas Bues

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Wood density is a variable influencing many of the technological and quality properties of wood. Understanding the pattern of wood density radial variation is important for its end-use. The X-ray technique, traditionally applied to softwood species to assess the wood quality properties, due to its simple and relatively uniform wood structure. On the other hand, very limited information is available about the validation of using this technique for hardwood species. The suitability of using the X-ray technique for the determination of hardwood density has a special significance in countries like Sudan, where only a few timbers are well known. This will not only save the time consumed by using the traditional methods, but it will also enhance the investigations of the great number of the lesser known species, the thing which will fill the huge cap of lake information of hardwood species growing in Sudan. The current study aimed to evaluate the validation of using the X-ray densitometry technique to determine the radial variation of wood density of Acacia seyal var. seyal. To this, a total of thirty trees were collected randomly from four states in Sudan. The wood density radial trend was determined using the basic density as well as density obtained by the X-ray densitometry method in order to assess the validation of X-ray technique in wood density radial variation determination. The results showed that the pattern of radial trend of density obtained by X-ray technique is very similar to that achieved by basic density. These results confirmed the validation of using the X-ray technique for Acacia seyal var. seyal density radial trend determination. It also promotes the suitability of using this method in other hardwood species.

Keywords: x-ray densitometry, wood density, Acacia seyal var. seyal, radial variation

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Authors: Ali Algryani

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Ellipsis involves the omission of an item or items that can be recovered from the preceding clause. Ellipsis is used as a cohesion marker; it enhances the cohesiveness of a text/discourse as a clause is interpretable only through making reference to an antecedent clause. The present study attempts to investigate the linguistic phenomenon of ellipsis from a translation perspective. It is mainly concerned with how ellipsis is translated from English into Arabic. The study covers different forms of ellipsis, such as noun phrase ellipsis, verb phrase ellipsis, gapping, pseudo-gapping, stripping, and sluicing. The primary aim of the study, apart from discussing the use and function of ellipsis, is to find out how such ellipsis phenomena are dealt with in English-Arabic translation and determine the implications of the translations of elliptical structures into Arabic. The study is based on the analysis of Dhofar University (DU) students' translations of sentences containing different forms of ellipsis. The initial findings of the study indicate that due to differences in syntactic structures and stylistic preferences between English and Arabic, Arabic tends to use lexical repetition in the translation of some elliptical structures, thus achieving a higher level of explicitness. This implies that Arabic tends to prefer lexical repetition to create cohesion more than English does. Furthermore, the study also reveals that the improper translation of ellipsis leads to interpretations different from those understood from the source text. Such mistranslations can be attributed to student translators’ lack of awareness of the use and function of ellipsis as well as the stylistic preferences of both languages. This has pedagogical implications on the teaching and training of translation students at DU. Students' linguistic competence needs to be enhanced through teaching linguistics-related issues with reference to translation and both languages, .i.e. source and target languages and with special emphasis on their use, function and stylistic preferences.

Keywords: cohesion, ellipsis, explicitness, lexical repetition

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Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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Authors: Rudi Kurniawan Arief

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Manufacturing cost and setup time are the hot topics to improve in Metal Stamping industry because material and components price are always rising up while costumer requires to cut down the component price year by year. The Single Minute Exchange of Die (SMED) is one of many methods to reduce waste in stamping industry. The Japanese Quick Die Change (QDC) dies system is one of SMED systems that could reduce both of setup time and manufacturing cost. However, this system is rarely used in stamping industries. This paper will analyze how deep the QDC dies system could reduce setup time and the manufacturing cost. The research is conducted by direct observation, simulating and comparing of QDC dies system with conventional dies system. In this research, we found that the QDC dies system could save up to 35% of manufacturing cost and reduce 70% of setup times. This simulation proved that the QDC die system is effective for cost reduction but must be applied in several parallel production processes.

Keywords: press die, metal stamping, QDC system, single minute exchange die, manufacturing cost saving, SMED

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Authors: Ahmed Noor Al-Qayyim

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During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Ahmed Najah Ahmed Al-Mahfoodh, Ali Najah Ahmed Al-Mahfoodh, Ahmed Al-Shafie

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In this study, genetic programming (GP) technique has been investigated in prediction of set of rainfall-runoff data. To assess the effect of input parameters on the model, the sensitivity analysis was adopted. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Correlation Coefficient (CC), Mean Square Error (MSE) and Correlation of Efficiency (CE). The principle aim of this study is to develop a computationally efficient and robust approach for predict of rainfall-runoff which could reduce the cost and labour for measuring these parameters. This research concentrates on the Johor River in Johor State, Malaysia.

Keywords: genetic programming, prediction, rainfall-runoff, Malaysia

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Authors: Jéssica Ferreira Rodrigues, Júlio Silvio De Sousa Bueno Filho, Vanessa Rios De Souza, Ana Carla Marques Pinheiro

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This study aimed to evaluate the implications of the block size and testing order on efficiency and precision of preference estimation for Dulce de leche samples. Efficiency was defined as the inverse of the average variance of pairwise comparisons among treatments. Precision was defined as the inverse of the variance of treatment means (or effects) estimates. The experiment was originally designed to test 16 treatments as a series of 8 Sudoku 16x16 designs being 4 randomized independently and 4 others in the reverse order, to yield balance in testing order. Linear mixed models were assigned to the whole experiment with 112 testers and all their grades, as well as their partially balanced subgroups, namely: a) experiment with the four initial EU; b) experiment with EU 5 to 8; c) experiment with EU 9 to 12; and b) experiment with EU 13 to 16. To record responses we used a nine-point hedonic scale, it was assumed a mixed linear model analysis with random tester and treatments effects and with fixed test order effect. Analysis of a cumulative random effects probit link model was very similar, with essentially no different conclusions and for simplicity, we present the results using Gaussian assumption. R-CRAN library lme4 and its function lmer (Fit Linear Mixed-Effects Models) was used for the mixed models and libraries Bayesthresh (default Gaussian threshold function) and ordinal with the function clmm (Cumulative Link Mixed Model) was used to check Bayesian analysis of threshold models and cumulative link probit models. It was noted that the number of samples tested in the same session can influence the acceptance level, underestimating the acceptance. However, proving a large number of samples can help to improve the samples discrimination.

Keywords: acceptance, block size, mixed linear model, testing order, testing order

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Authors: Praveen Kumar, Satish Kumar, Jashanpreet Singh

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Transportation of unrefined crude oil from the production unit to a refinery or large storage area by a pipeline is difficult due to the different properties of crude in various areas. Thus, the design of a crude oil pipeline is a very complex and time consuming process, when considering all the various parameters. There were three very important parameters that play a significant role in the transportation and processing pipeline design; these are: viscosity profile, temperature profile and the velocity profile of waxy crude oil through the crude oil pipeline. Knowledge of the Rheological computational technique is required for better understanding the flow behavior and predicting the flow profile in a crude oil pipeline. From these profile parameters, the material and the emulsion that is best suited for crude oil transportation can be predicted. Rheological computational fluid dynamic technique is a fast method used for designing flow profile in a crude oil pipeline with the help of computational fluid dynamics and rheological modeling. With this technique, the effect of fluid properties including shear rate range with temperature variation, degree of viscosity, elastic modulus and viscous modulus was evaluated under different conditions in a transport pipeline. In this paper, two crude oil samples was used, as well as a prepared emulsion with natural and synthetic additives, at different concentrations ranging from 1,000 ppm to 3,000 ppm. The rheological properties was then evaluated at a temperature range of 25 to 60 °C and which additive was best suited for transportation of crude oil is determined. Commercial computational fluid dynamics (CFD) has been used to generate the flow, velocity and viscosity profile of the emulsions for flow behavior analysis in crude oil transportation pipeline. This rheological CFD design can be further applied in developing designs of pipeline in the future.

Keywords: surfactant, natural, crude oil, rheology, CFD, viscosity

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Authors: Archana Thangavelu, Han-Ik Park, Young-Chul Park, Joon-Hong Park

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In this numerical study, we have proposed a method for evaluation of backward extrusion process of pressure vessel made up of steel. Demand for lighter and stiffer products have been increasing in the last years especially in automobile engineering. Through detailed finite element analysis, effective stress, strain and velocity profile have been obtained with optimal range. The process design of a forward and backward extrusion axe-symmetric part has been studied. Forging is mainly carried out because forged products are highly reliable and possess superior mechanical properties when compared to normal products. Performing computational simulations of 3D hot forging with various dimensions of billet and optimization of weight is carried out using Taguchi Orthogonal Array (OA) Optimization technique. The technique used in this study can be used for newly developed materials to investigate its forgeability for much complicated shapes in closed hot die forging process.

Keywords: backward extrusion, hot forging, optimization, finite element analysis, Taguchi method

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Authors: Yuyang Cheng, Marcos Escobar-Anel

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This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.

Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem

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Authors: Ehsan Gholamalizadeh, Jae Dong Chung

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Solar chimney power plant is a feasible solar thermal system which produces electricity from the Sun. The objective of this study is to investigate buoyancy-driven flow and heat transfer through a built pilot solar chimney system called 'Kerman Project'. The system has a chimney with the height and diameter of 60 m and 3 m, respectively, and the average radius of its solar collector is about 20 m, and also its average collector height is about 2 m. A three-dimensional simulation was conducted to analyze the system, using computational fluid dynamics (CFD). In this model, radiative transfer equation was solved using the discrete ordinates (DO) radiation model taking into account a non-gray radiation behavior. In order to modelling solar irradiation from the sun’s rays, the solar ray tracing algorithm was coupled to the computation via a source term in the energy equation. The model was validated with comparing to the experimental data of the Manzanares prototype and also the performance of the built pilot system. Then, based on the numerical simulations, velocity and temperature distributions through the system, the temperature profile of the ground surface and the system performance were presented. The analysis accurately shows the flow and heat transfer characteristics through the pilot system and predicts its performance.

Keywords: buoyancy-driven flow, computational fluid dynamics, heat transfer, renewable energy, solar chimney power plant

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Authors: Rawinun Praserttaweelap, Somyot Kiatwanidvilai

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Obstacle avoidance is the one key for the robot system in unknown environment. The robots should be able to know their position and safety region. This research starts on the path planning which are SLAM and AMCL in ROS system. In addition, the best parameters of the obstacle avoidance function are required. In situation on Hard Disk Drive Manufacturing, the distance between robots and obstacles are very serious due to the manufacturing constraint. The simulations are accomplished by the SLAM and AMCL with adaptive velocity and safety region calculation.

Keywords: obstacle avoidance, OA, Simultaneous Localization and Mapping, SLAM, Adaptive Monte Carlo Localization, AMCL, KLD sampling, KLD

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Authors: Amine Ben Slama, Aymen Mouelhi, Sondes Manoubi, Chiraz Mbarek, Hedi Trabelsi, Mounir Sayadi, Farhat Fnaiech

Abstract:

Vertigo is a sensation of feeling off balance; the cause of this symptom is very difficult to interpret and needs a complementary exam. Generally, vertigo is caused by an ear problem. Some of the most common causes include: benign paroxysmal positional vertigo (BPPV), Meniere's disease and vestibular neuritis (VN). In clinical practice, different tests of videonystagmographic (VNG) technique are used to detect the presence of vestibular neuritis (VN). The topographical diagnosis of this disease presents a large diversity in its characteristics that confirm a mixture of problems for usual etiological analysis methods. In this study, a vestibular neuritis analysis method is proposed with videonystagmography (VNG) applications using an estimation of pupil movements in the case of an uncontrolled motion to obtain an efficient and reliable diagnosis results. First, an estimation of the pupil displacement vectors using with Hough Transform (HT) is performed to approximate the location of pupil region. Then, temporal and frequency features are computed from the rotation angle variation of the pupil motion. Finally, optimized features are selected using Fisher criterion evaluation for discrimination and classification of the VN disease.Experimental results are analyzed using two categories: normal and pathologic. By classifying the reduced features using the Support Vector Machine (SVM), 94% is achieved as classification accuracy. Compared to recent studies, the proposed expert system is extremely helpful and highly effective to resolve the problem of VNG analysis and provide an accurate diagnostic for medical devices.

Keywords: nystagmus, vestibular neuritis, videonystagmographic system, VNG, Fisher criterion, support vector machine, SVM

Procedia PDF Downloads 139

Authors: Amin Noor, Roslinda Nazar, Norihan Md. Arifin

Abstract:

In this paper, a numerical and theoretical study has been performed for the stagnation-point boundary layer flow and heat transfer towards a shrinking sheet in a nanofluid. The mathematical nanofluid model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Numerical results are obtained for the skin friction coefficient, the local Nusselt number as well as the velocity and temperature profiles for some values of the governing parameters, namely the nanoparticle volume fraction Φ, the shrinking parameter λ and the Prandtl number Pr. Three different types of nanoparticles are considered, namely Cu, Al2O3 and TiO2. It is found that solutions do not exist for larger shrinking rates and dual (upper and lower branch) solutions exist when λ < -1.0. A stability analysis has been performed to show which branch solutions are stable and physically realizable. It is also found that the upper branch solutions are stable while the lower branch solutions are unstable.

Keywords: heat transfer, nanofluid, shrinking sheet, stability analysis, stagnation-point flow

Procedia PDF Downloads 382

Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

Abstract:

Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

Procedia PDF Downloads 160

Authors: Aminu Hamza

Abstract:

This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

Procedia PDF Downloads 306

Authors: Weichao Yu, Kai Wen, Weihe Huang, Yang Yang, Jing Gong

Abstract:

Metal-loss corrosion is a major threat to the safety and integrity of gas pipelines as it may result in the burst failures which can cause severe consequences that may include enormous economic losses as well as the personnel casualties. Therefore, it is important to ensure the corroding pipeline integrity and efficiency, considering the value of wall thickness, which plays an important role in the failure probability of corroding pipeline. Actually, the wall thickness is controlled during pipe purchase stage. For example, the API_SPEC_5L standard regulates the allowable tolerance of the wall thickness from the specified value during the pipe purchase. The allowable wall thickness tolerance will be used to determine the wall thickness distribution characteristic such as the mean value, standard deviation and distribution. Taking the uncertainties of the input variables in the burst limit-state function into account, the reliability approach rather than the deterministic approach will be used to evaluate the failure probability. Moreover, the cost of pipe purchase will be influenced by the allowable wall thickness tolerance. More strict control of the wall thickness usually corresponds to a higher pipe purchase cost. Therefore changing the wall thickness tolerance will vary both the probability of a burst failure and the cost of the pipe. This paper describes an approach to optimize the wall thickness tolerance considering both the safety and economy of corroding pipelines. In this paper, the corrosion burst limit-state function in Annex O of CSAZ662-7 is employed to evaluate the failure probability using the Monte Carlo simulation technique. By changing the allowable wall thickness tolerance, the parameters of the wall thickness distribution in the limit-state function will be changed. Using the reliability approach, the corresponding variations in the burst failure probability will be shown. On the other hand, changing the wall thickness tolerance will lead to a change in cost in pipe purchase. Using the variation of the failure probability and pipe cost caused by changing wall thickness tolerance specification, the optimal allowable tolerance can be obtained, and used to define pipe purchase specifications.

Keywords: allowable tolerance, corroding pipeline segment, operation cost, production cost, reliability approach

Procedia PDF Downloads 396