Search results for: thermal influence of boundary parameters

Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: Cascade control, multi-loop control systems, multi-objective optimization, optimal control.

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Authors: H. Zarei, M. H. Fazel Zarandi, M. Karbasian

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A Decision Support System/Expert System for stock portfolio selection presented where at first step, both technical and fundamental data used to estimate technical and fundamental return and risk (1st phase); Then, the estimated values are aggregated with the investor preferences (2nd phase) to produce convenient stock portfolio. In the 1st phase, there are two expert systems, each of which is responsible for technical or fundamental estimation. In the technical expert system, for each stock, twenty seven candidates are identified and with using rough sets-based clustering method (RC) the effective variables have been selected. Next, for each stock two fuzzy rulebases are developed with fuzzy C-Mean method and Takai-Sugeno- Kang (TSK) approach; one for return estimation and the other for risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation method. In parallel, for fundamental expert systems, fuzzy rule-bases have been identified in the form of “IF-THEN" rules through brainstorming with the stock market experts and the input data have been derived from financial statements; as a result two fuzzy rule-bases have been generated for all the stocks, one for return and the other for risk. In the 2nd phase, user preferences represented by four criteria and are obtained by questionnaire. Using an expert system, four estimated values of return and risk have been aggregated with the respective values of user preference. At last, a fuzzy rule base having four rules, treats these values and produce a ranking score for each stock which will lead to a satisfactory portfolio for the user. The stocks of six manufacturing companies and the period of 2003-2006 selected for data gathering.

Keywords: Stock Portfolio Selection, Fuzzy Rule-Base ExpertSystems, Financial Decision Support Systems, Technical Analysis, Fundamental Analysis.

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Authors: Jazaul Ikhsan, Masaharu Fujita

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Safety, river environment, and sediment utilization are the elements of the target of sediment management. As a change in an element by sediment management, may affect the other two elements, and the priority among three elements depends on stakeholders. It is necessary to develop a method to evaluate the effect of sediment management on each element and an integrated evaluation method for socio-economic effect. In this study, taking Mount Merapi basin as an investigation field, the method for an active volcanic basin was developed. An integrated evaluation method for sediment management was discussed from a socio-economic point on safety, environment, and sediment utilization and a case study of sediment management was evaluated by means of this method. To evaluate the effect of sediment management, some parameters on safety, utilization, and environment have been introduced. From a utilization point of view, job opportunity, additional income of local people, and tax income to local government were used to evaluate the effectiveness of sediment management. The risk degree of river infrastructure was used to describe the effect of sediment management on a safety aspect. To evaluate the effects of sediment management on environment, the mean diameter of grain size distribution of riverbed surface was used. On the coordinate system designating these elements, the direction of change in basin condition by sediment management can be predicted, so that the most preferable sediment management can be decided. The results indicate that the cases of sediment management tend to give the negative impacts on sediment utilization. However, these sediment managements will give positive impacts on safety and environment condition. Evaluation result from a social-economic point of view shows that the case study of sediment management reduces job opportunity and additional income for inhabitants as well as tax income for government. Therefore, it is necessary to make another policy for creating job opportunity for inhabitants to support these sediment managements.

Keywords: Merapi, sediment, management, evaluation

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: Apparent porosity, beneficiation, low grade chromite, refractory, spinel compounds, slag resistance.

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Authors: Roy R. Gu, Mahesh Sahu, Xianggui Zhao

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Contour filter strips planted with perennial vegetation can be used to improve surface and ground water quality by reducing pollutant, such as NO3-N, and sediment outflow from cropland to a river or lake. Meanwhile, the filter strips of perennial grass with biofuel potentials also have economic benefits of producing ethanol. In this study, The Soil and Water Assessment Tool (SWAT) model was applied to the Walnut Creek Watershed to examine the effectiveness of contour strips in reducing NO3-N outflows from crop fields to the river or lake. Required input data include watershed topography, slope, soil type, land-use, management practices in the watershed and climate parameters (precipitation, maximum/minimum air temperature, solar radiation, wind speed and relative humidity). Numerical experiments were conducted to identify potential subbasins in the watershed that have high water quality impact, and to examine the effects of strip size and location on NO3-N reduction in the subbasins under various meteorological conditions (dry, average and wet). Variable sizes of contour strips (10%, 20%, 30% and 50%, respectively, of a subbasin area) planted with perennial switchgrass were selected for simulating the effects of strip size and location on stream water quality. Simulation results showed that a filter strip having 10%-50% of the subbasin area could lead to 55%- 90% NO3-N reduction in the subbasin during an average rainfall year. Strips occupying 10-20% of the subbasin area were found to be more efficient in reducing NO3-N when placed along the contour than that when placed along the river. The results of this study can assist in cost-benefit analysis and decision-making in best water resources management practices for environmental protection.

Keywords: modeling, SWAT, water quality, NO3-N, watershed.

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Authors: Akhtar N, Khan BA, Khan MS, Mahmood T, Khan HMS, Iqbal M, Bashir S

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This study was designed to formulate, pharmaceutically evaluate a topical skin-care cream (w/o emulsion) of Aloe Vera versus its vehicle (Base) as control and determine their effects on Stratum Corneum (SC) water content and Transepidermal water loss (TEWL). Base containing no extract and a Formulation containing 3% concentrated extract of Aloe Vera was developed by entrapping in the inner aqueous phase of w/o emulsion (cream). Lemon oil was incorporated to improve the odor. Both the Base and Formulation were stored at 8°C ±0.1°C (in refrigerator), 25°C±0.1°C, 40°C±0.1°C and 40°C± 0.1°C with 75% RH (in incubator) for a period of 4 weeks to predict their stability. The evaluation parameters consisted of color, smell, type of emulsion, phase separation, electrical conductivity, centrifugation, liquefaction and pH. Both the Base and Formulation were applied to the cheeks of 21 healthy human volunteers for a period of 8 weeks Stratum corneum (SC) water content and Transepidermal water loss (TEWL) were monitored every week to measure any effect produced by these topical creams. The expected organoleptic stability of creams was achieved from 4 weeks in-vitro study period. Odor was disappeared with the passage of time due to volatilization of lemon oil. Both the Base and Formulation produced significant (p≤0.05) changes in TEWL with respect to time. SC water content was significantly (p≤0.05) increased by the Formulation while the Base has insignificant (p 0.05) effects on SC water content. The newly formulated cream of Aloe Vera, applied is suitable for improvement and quantitative monitoring of skin hydration level (SC water content/ moisturizing effects) and reducing TEWL in people with dry skin.

Keywords: Aloe Vera; Skin; Stratum corneum (SC) water content and Transepidermal water loss (TEWL).

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Authors: Ola I. S. El Dardery, Ismail Gomaa, Adel R. M. Rayan, Ghada El Khayat, Sara H. Sabry

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Continuous improvement activities are becoming a key organizational success factor; those improvement activities include but are not limited to kaizen, six sigma, lean production, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This research aims at proposing a measuring system for kaizen activities from a sustainable balanced scorecard perspective. A survey was developed and disseminated among kaizen experts in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five sustainable balanced scorecard perspectives. This research contributes to the extant literature by presenting a kaizen measurement of both kaizen process and results that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation across various sectors and industries. Thus, grasping the full benefits of kaizen implementation will contribute to the spread of kaizen understanding and practice. Also, this research provides insights on the social and cultural differences that would influence the kaizen success. Determining the combination of the proper kaizen measures could be used by any industry, whether service or manufacturing for better kaizen activities measurement. The comparison between Japanese implementation of kaizen, as the pioneers of continuous improvement, and Egyptian implementation will help recommending better practices of kaizen in Egypt and contributing to the 2030 sustainable development goals. The study results reveal that there is no significant difference in allocating kaizen benefits between Egypt and Japan. However, with regard to the critical success factors some differences appeared reflecting the social differences and understanding between both countries, a single integrated measurement was reached between the Egyptian and Japanese allocation highlighting the Japanese experts’ opinion as the ultimate criterion for selection.

Keywords: continuous improvements, kaizen, performance, sustainable balanced scorecard

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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Authors: T. Kumar, Achinta Bera, Ajay Mandal

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Use of microemulsion in enhanced oil recovery has become more attractive in recent years because of its high level of extraction efficiency. Experimental investigations have been made on characterization of microemulsions of oil-brinesurfactant/ cosurfactant system for its use in enhanced oil recovery (EOR). Sodium dodecyl sulfate, propan-1-ol and heptane were selected as surfactant, cosurfactant and oil respectively for preparation of microemulsion. The effects of salinity on the relative phase volumes and solubilization parameters have also been studied. As salinity changes from low to high value, phase transition takes place from Winsor I to Winsor II via Winsor III. Suitable microemulsion composition has been selected based on its stability and ability to reduce interfacial tension. A series of flooding experiments have been performed using the selected microemulsion. The flooding experiments were performed in a core flooding apparatus using uniform sand pack. The core holder was tightly packed with uniform sands (60-100 mesh) and saturated with brines of different salinities. It was flooded with the brine at 25 psig and the absolute permeability was calculated from the flow rate of the through sand pack. The sand pack was then flooded with the crude oil at 800 psig to irreducible water saturation. The initial water saturation was determined on the basis of mass balance. Waterflooding was conducted by placing the coreholder horizontally at a constant injection pressure at 200 pisg. After water flooding, when water-cut reached above 95%, around 0.5 pore volume (PV) of the above microemulsion slug was injected followed by chasing water. The experiments were repeated using different composition of microemulsion slug. The additional recoveries were calculated by material balance. Encouraging results with additional recovery more than 20% of original oil in place above the conventional water flooding have been observed.

Keywords: Microemulsion Flooding, Enhanced Oil Recovery, Phase Behavior, Optimal salinity

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Authors: Miguel A. Gómez, Enrique Hilario, Francisco J. Alvarez, Elena Gastiasoro, Antonia Alvarez, Jose A. Casla, Jorge Arguinchona, Juan L. Larrabe

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Total liquid ventilation can support gas exchange in animal models of lung injury. Clinical application awaits further technical improvements and performance verification. Our aim was to develop a liquid ventilator, able to deliver accurate tidal volumes, and a computerized system for measuring lung mechanics. The computer-assisted, piston-driven respirator controlled ventilatory parameters that were displayed and modified on a real-time basis. Pressure and temperature transducers along with a lineal displacement controller provided the necessary signals to calculate lung mechanics. Ten newborn lambs (<6 days old) with respiratory failure induced by lung lavage, were monitored using the system. Electromechanical, hydraulic and data acquisition/analysis components of the ventilator were developed and tested in animals with respiratory failure. All pulmonary signals were collected synchronized in time, displayed in real-time, and archived on digital media. The total mean error (due to transducers, A/D conversion, amplifiers, etc.) was less than 5% compared to calibrated signals. Improvements in gas exchange and lung mechanics were observed during liquid ventilation, without impairment of cardiovascular profiles. The total liquid ventilator maintained accurate control of tidal volumes and the sequencing of inspiration/expiration. The computerized system demonstrated its ability to monitor in vivo lung mechanics, providing valuable data for early decision-making.

Keywords: Immature lamb, perfluorocarbon, pressure-limited, total liquid ventilation, ventilator, volume-controlled.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: Wan-I Lee, Nelio Mendoza Figueredo

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The impact of COVID-19 has a significant effect on all sectors of society globally. Health information technology (HIT) has become an effective health strategy in this age of distancing. In this regard, Mobile Health (mHealth) plays a critical role in managing patient and provider workflows during the COVID-19 pandemic. Therefore, the users' perception of service quality about mHealth services plays a significant role in shaping confidence and subsequent behaviors regarding the mHealth users' intention of use. This study's objective was to explore levels of user attributes analyzed by a qualitative method of how health practitioners and patients are satisfied or dissatisfied with using mHealth services; and analyzed the users' intention in the context of Taiwan during the COVID-19 pandemic. This research explores the experienced usability of a mHealth services during the Covid-19 pandemic. This study uses qualitative methods that include in-depth and semi-structured interviews that investigate participants' perceptions and experiences and the meanings they attribute to them. The five cases consisted of health practitioners, clinic staff, and patients' experiences using mHealth services. This study encourages participants to discuss issues related to the research question by asking open-ended questions, usually in one-to-one interviews. The findings show the positive and negative attributes of mHealth service quality. Hence, the significant importance of patients' and health practitioners' issues on several dimensions of perceived service quality is system quality, information quality, and interaction quality. A concept map for perceptions regards to emergency uses' intention of mHealth services process is depicted. The findings revealed that users pay more attention to "Medical care", "ease of use" and "utilitarian benefits" and have less importance for "Admissions and Convenience" and "Social influence". To improve mHealth services, the mHealth providers and health practitioners should better manage users' experiences to enhance mHealth services. This research contributes to the understanding of service quality issues in mHealth services during the COVID-19 pandemic.

Keywords: COVID-19, mobile health, mHealth, service quality, use intention.

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Authors: Wei-Hsin Sun, Jr-Ming Miao, Chang-Hsien Tai, Chien-Chun Hung

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The development of biomimetic micro-aerial-vehicles (MAVs) with flapping wings is the future trend in military/domestic field. The successful flight of MAVs is strongly related to the understanding of unsteady aerodynamic performance of low Reynolds number airfoils under dynamic flapping motion. This study explored the effects of flapping frequency, stroke amplitude, and the inclined angle of stroke plane on lift force and thrust force of a bio-inspiration corrugated airfoil with 33 full factorial design of experiment and ANOVA analysis. Unsteady vorticity flows over a corrugated thin airfoil executing flapping motion are computed with time-dependent two-dimensional laminar incompressible Reynolds-averaged Navier-Stokes equations with the conformal hybrid mesh. The tested freestream Reynolds number based on the chord length of airfoil as characteristic length is fixed of 103. The dynamic mesh technique is applied to model the flapping motion of a corrugated airfoil. Instant vorticity contours over a complete flapping cycle clearly reveals the flow mechanisms for lift force generation are dynamic stall, rotational circulation, and wake capture. The thrust force is produced as the leading edge vortex shedding from the trailing edge of airfoil to form a reverse von Karman vortex. Results also indicated that the inclined angle is the most significant factor on both the lift force and thrust force. There are strong interactions between tested factors which mean an optimization study on parameters should be conducted in further runs.

Keywords: biomimetic, MAVs, aerodynamic, ANOVA analysis.

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Authors: Yan Su, L. C. Chan

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A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.

Keywords: Grid Connected, RMSD, Solar PV System, Typical Day.

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: Liquefaction, alkaline catalysis, optimization, Quercus cerris bark.

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: Almost strictly positive real, doubly-fed induction generator, simple adaptive control, subsynchronous oscillations, wind turbine.

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

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In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer. 

Keywords: Surface hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness.

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Authors: S. M. Abdul Khader, Anurag Ayachit, Raghuvir Pai, K. A. Ahmed, V. R. K. Rao, S. Ganesh Kamath

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The numerical simulation has made tremendous advances in investigating the blood flow phenomenon through elastic arteries. Such study can be useful in demonstrating the disease progression and hemodynamics of cardiovascular diseases such as atherosclerosis. In the present study, patient specific case diagnosed with partially stenosed complete right ICA and normal left carotid bifurcation without any atherosclerotic plaque formation is considered. 3D patient specific carotid bifurcation model is generated based on CT scan data using MIMICS-4.0 and numerical analysis is performed using FSI solver in ANSYS-14.5. The blood flow is assumed to be incompressible, homogenous and Newtonian, while the artery wall is assumed to be linearly elastic. The two-way sequentially coupled transient FSI analysis is performed using FSI solver for three pulse cycles. The hemodynamic parameters such as flow pattern, Wall Shear Stress, pressure contours and arterial wall deformation are studied at the bifurcation and critical zones such as stenosis. The variation in flow behavior is studied throughout the pulse cycle. Also, the simulation results reveal that there is a considerable increase in the flow behavior in stenosed carotid in contrast to the normal carotid bifurcation system. The investigation also demonstrates the disturbed flow pattern especially at the bifurcation and stenosed zone elevating the hemodynamics, particularly during peak systole and later part of the pulse cycle. The results obtained agree well with the clinical observation and demonstrates the potential of patient specific numerical studies in prognosis of disease progression and plaque rupture.

Keywords: Fluid-Structure Interaction, arterial stenosis, Wall Shear Stress, Carotid Artery Bifurcation.

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: Block caving, ground penetrating radar, reflectivity, RQD.

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: Antioxidant activity, corn oil, oxidative deterioration, pomegranate.

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

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Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: Additive manufacturing, lean production, reproducibility, work safety.

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: Smart grid, EHV transmission tower, response spectrum, damage level monitoring.

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Authors: Chigbogu G. Ozoegwu, Sam N. Omenyi

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The objective in this work is to generate and discuss the stability results of fully-immersed end-milling process with parameters; tool mass m=0.0431kg,tool natural frequency ω_n = 5700 rads^-1, damping factor ξ=0.002 and workpiece cutting coefficient C=3.5x10^7 Nm^-7/4. Different no of teeth is considered for the end-milling. Both 1-DOF and 2-DOF chatter models of the system are generated on the basis of non-linear force law. Chatter stability analysis is carried out using a modified form (generalized for both 1-DOF and 2-DOF models) of recently developed method called Full-discretization. The full-immersion three tooth end-milling together with higher toothed end-milling processes has secondary Hopf bifurcation lobes (SHBL’s) that exhibit one turning (minimum) point each. Each of such SHBL is demarcated by its minimum point into two portions; (i) the Lower Spindle Speed Portion (LSSP) in which bifurcations occur in the right half portion of the unit circle centred at the origin of the complex plane and (ii) the Higher Spindle Speed Portion (HSSP) in which bifurcations occur in the left half portion of the unit circle. Comments are made regarding why bifurcation lobes should generally get bigger and more visible with increase in spindle speed and why flip bifurcation lobes (FBL’s) could be invisible in the low-speed stability chart but visible in the high-speed stability chart of the fully-immersed three-tooth miller.

Keywords: Chatter, flip bifurcation, modified full-discretization map stability lobe, secondary Hopf bifurcation.

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Authors: F. J. Moral García, P. Valiente González, F. López Rodríguez

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Ground-level tropospheric ozone is one of the air pollutants of most concern. It is mainly produced by photochemical processes involving nitrogen oxides and volatile organic compounds in the lower parts of the atmosphere. Ozone levels become particularly high in regions close to high ozone precursor emissions and during summer, when stagnant meteorological conditions with high insolation and high temperatures are common. In this work, some results of a study about urban ozone distribution patterns in the city of Badajoz, which is the largest and most industrialized city in Extremadura region (southwest Spain) are shown. Fourteen sampling campaigns, at least one per month, were carried out to measure ambient air ozone concentrations, during periods that were selected according to favourable conditions to ozone production, using an automatic portable analyzer. Later, to evaluate the ozone distribution at the city, the measured ozone data were analyzed using geostatistical techniques. Thus, first, during the exploratory analysis of data, it was revealed that they were distributed normally, which is a desirable property for the subsequent stages of the geostatistical study. Secondly, during the structural analysis of data, theoretical spherical models provided the best fit for all monthly experimental variograms. The parameters of these variograms (sill, range and nugget) revealed that the maximum distance of spatial dependence is between 302-790 m and the variable, air ozone concentration, is not evenly distributed in reduced distances. Finally, predictive ozone maps were derived for all points of the experimental study area, by use of geostatistical algorithms (kriging). High prediction accuracy was obtained in all cases as cross-validation showed. Useful information for hazard assessment was also provided when probability maps, based on kriging interpolation and kriging standard deviation, were produced.

Keywords: Kriging, map, tropospheric ozone, variogram.

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Authors: Fereshteh M. Haskouei, Habib Alimohammadian

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Magnetic susceptibility (χ) is operational to identify of late quaternary glacial-interglacial cycles in loess-paleosol sequences. It is well accepted that many loess-paleosol sequences bear witness to cold-dry/warm-humid periods, well known as glacial-interglacial cycles, respectively. For this study, loess-paleosol sequence of north-east of Iran was magnetically investigated. The study area is situated at about 8 km away of Neka city, on the main road of Sari-Behshahr, in Mazandaran Province, north of Iran. The youngest deposits of study area are the late Quaternary wind-blown accumulations. In this study, the total number of 117 samples was collected from loess-paleosols units. After that, the natural remnant magnetization (NRM) and magnetic susceptibility (MS) of the samples were measured. Variation of MS of more than 110 loess samples was plotted to reveal the correlation of the MS and paleoclimatic changes. This study aims reconstruction of climatic changes (glacial-interglacial and stadials-interstadials cycles). To confirm our results we compared MS (χ) and the curves of other investigations in paleoclimatology. This correspondence abled us to recognize worldly events in the study area such as: Younger Dryas, the Last Glacial Maximum (LGM), deglaciation of Northern Hemisphere etc. The obtained magnetic data indicate that during almost 50 ka, at least two glacial-interglacial periods occurred in north-east of Iran. Further, variation of χ values revealed short period of climatically cycles known as stadials-interstadials. We recognized 4 stadials and a single stadial as colder sub-periods for S₀ (recently soil-paleosol) and S₂ (lower paleosol), respectively, Moreover, we recognized 6 warmer sub-periods (interstadials) for L₁ (upper loess) and one interstadial L₂ (lower loess).

Keywords: Glacial-interglacial cycles, Iran, last glacial maximum, loess, magnetic susceptibility (χ), Neka, Stadials-Interstadials sub-periods, younger dryas.

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent’s attributes. Also, the influence of social networks in the developing of agents interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: Artificial stock markets, agent based simulation, bounded rationality, behavioral finance, artificial neural network, interaction, scale-free networks.

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Authors: Prabhat Ranjan Prem, B.H.Bharatkumar, Nagesh R Iyer

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A research program is conducted to evaluate the mechanical properties of Ultra High Performance Concrete, target compressive strength at the age of 28 days being more than 150 MPa. The methodology to develop such mix has been explained. The material properties, mix design and curing regime are determined. The material attributes are understood by studying the stress strain behaviour of UHPC cylinders under uniaxial compressive loading. The load –crack mouth opening displacement (cmod) of UHPC beams, flexural strength and fracture energy was evaluated using third point loading test. Compressive strength and Split tensile strength results are determined to find out the compressive and tensile behaviour. Residual strength parameters are presented vividly explaining the flexural performance, toughness of concrete.Durability studies were also done to compare the effect of fibre to that of a control mix For all the studies the Mechanical properties were evaluated by varying the percentage and aspect ratio of steel fibres The results reflected that higher aspect ratio and fibre volume produced drastic changes in the cube strength, cylinder strength, post peak response, load-cmod, fracture energy flexural strength, split tensile strength, residual strength and durability. In regards to null application of UHPC in India, an initiative is undertaken to comprehend the mechanical behaviour of UHPC, which will be vital for longer run in commercialization for structural applications.

Keywords: Ultra High Performance Concrete, Reinforcement Index, Compressive Strength, Tensile Strength, Flexural Strength, Residual Strength, Fracture Energy, Stress-Strain Relationships, Load-Crack Mouth Opening Displacement and Durability.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Guclu Insel, Efe Gumuslu, Gulten Yuksek, Nilay Sayi Ucar, Emine Ubay Cokgor, Tugba Olmez Hanci, Didem Okutman Tas, Fatos Germirli Babuna, Derya Firat Ertem, Okmen Yildirim, Ozge Erturan, Betul Kirci

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In order to eliminate water scarcity problems, effective precautions must be taken. Growing competition for water is increasingly forcing facilities to tackle their own water scarcity problems. At this point, application of wastewater reclamation and reuse results in considerable economic advantageous. In this study, an enamel coating facility, which is one of the high water consumed facilities, is evaluated in terms of its wastewater reuse potential. Wastewater reclamation and reuse can be defined as one of the best available techniques for this sector. Hence, process and pollution profiles together with detailed characterization of segregated wastewater sources are appraised in a way to find out the recoverable effluent streams arising from enamel coating operations. Daily, 170 m³ of process water is required and 160 m³ of wastewater is generated. The segregated streams generated by two enamel coating processes are characterized in terms of conventional parameters. Relatively clean segregated wastewater streams (reusable wastewaters) are separately collected and experimental treatability studies are conducted on it. The results reflected that the reusable wastewater fraction has an approximate amount of 110 m³/day that accounts for 68% of the total wastewaters. The need for treatment applicable on reusable wastewaters is determined by considering water quality requirements of various operations and characterization of reusable wastewater streams. Ultra-filtration (UF), Nano-filtration (NF) and Reverse Osmosis (RO) membranes are subsequently applied on reusable effluent fraction. Adequate organic matter removal is not obtained with the mentioned treatment sequence.

Keywords: enamel coating, membrane, reuse, wastewater

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modeling has constantly been a challenge through history for human beings. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: Auto-calibration, Gilan, Large-Scale Water Resources, Simulation.

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