Search results for: optimal parameters

Authors: D. Deepak, N. Yagnesh Sharma

Abstract:

Abrasive Water Jet (AWJ) machining is a relatively new nontraditional machine tool used in machining of fiber reinforced composite. The quality of machined surface depends on jet exit kinetic energy which depends on various operating and material parameters. In the present work the effect abrasive parameters such as its size, concentration and type on jet kinetic energy is investigated using computational fluid dynamics (CFD). In addition, the effect of these parameters on wall shear stress developed inside the nozzle is also investigated. It is found that for the same operating parameters, increase in the abrasive volume fraction (concentration) results in significant decrease in the wall shear stress as well as the jet exit kinetic energy. Increase in the abrasive particle size results in marginal decrease in the jet exit kinetic energy. Numerical simulation also indicates that garnet abrasives produce better jet exit kinetic energy than aluminium oxide and silicon carbide.

Keywords: abrasive water jet machining, jet kinetic energy, operating pressure, wall shear stress, Garnet abrasive

Procedia PDF Downloads 361

Authors: Shakir Mamedov, Tukezban Hasanova

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Research of dynamic properties of various materials and elements of structures at shock affecting and on the waves so many scientific works of the Azerbaijani scientists are devoted. However, Experimental definition of dynamic parameters of fluctuations of constructions and buildings while carries estimated character. The purpose of the present experimental researches is definition of parameters of fluctuations of installation of observations. In this case, a mockup of four floor buildings and sixteen floor skeleton-type buildings built in the Baku with the stiffening diaphragm at natural vibrating seismic affectings.

Keywords: fluctuations, seismoreceivers, dynamic experiments, acceleration

Procedia PDF Downloads 378

Authors: S. Botman, D. Borchevkin, V. Petrov, E. Bogdanov, M. Patrushev, N. Shusharina

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In this paper, we report the development of the device for diagnostics of cardiovascular system state and associated automated workstation for large-scale medical measurement data collection and analysis. It was shown that optimal design for the monitoring device is wristband as it represents engineering trade-off between accuracy and usability. The monitoring device is based on the infrared reflective photoplethysmographic sensor, which allows collecting multiple physiological parameters, such as heart rate and pulsing wave characteristics. Developed device use BLE interface for medical and supplementary data transmission to the coupled mobile phone, which process it and send it to the doctor's automated workstation. Results of this experimental model approbation confirmed the applicability of the proposed approach.

Keywords: cardiovascular diseases, health monitoring systems, photoplethysmography, pulse wave, remote diagnostics

Procedia PDF Downloads 479

Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process

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Authors: Refal Hussain, Saifuddin M. Nomanbhay

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Glycerol is a valuable raw material for the production of industrially useful metabolites. Among many promising applications for the use of glycerol is its bioconversion to high value-added compounds, such as bioethanol through microbial fermentation. Bioethanol is an important industrial chemical with emerging potential as a biofuel to replace vanishing fossil fuels. The yield of liquid fuel in this process was greatly influenced by various parameters viz, temperature, pH, glycerol concentration, organic concentration, and agitation speed were considered. The present study was undertaken to investigate optimum parameters for bioethanol production from raw glycerol by immobilized mutant Escherichia coli (E.coli) (ATCC11505) strain on chitosan cross linked glutaraldehyde optimized by Taguchi statistical method in shake flasks. The initial parameters were set each at four levels and the orthogonal array layout of L16 (45) conducted. The important controlling parameters for optimized the operational fermentation was temperature 38 °C, medium pH 6.5, initial glycerol concentration (250 g/l), and organic source concentration (5 g/l). Fermentation with optimized parameters was carried out in a custom fabricated shake flask. The predicted value of bioethanol production under optimized conditions was (118.13 g/l). Immobilized cells are mainly used for economic benefits of continuous production or repeated use in continuous as well as in batch mode.

Keywords: bioethanol, Escherichia coli, immobilization, optimization

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Authors: H. A. Taner, V. Önen

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A suitable choice of flotation parameters and reagents have a strong effect on the effectiveness of flotation process. The objective of this paper is to give an overview of the flotation of chalcopyrite with the different conditions and dispersants. Flotation parameters such as grinding time, pH, type, and dosage of dispersant were investigated. In order to understand the interaction of some dispersants, sodium silicate, sodium hexametaphosphate and sodium polyphosphate were used. The optimum results were obtained at a pH of 11.5 and a grinding time of 10 minutes. A copper concentrate was produced assaying 29.85% CuFeS₂ and 65.97% flotation recovery under optimum rougher flotation conditions with sodium silicate.

Keywords: chalcopyrite, dispersant, flotation, reagent

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Authors: Mohammad Mehdi Mazarei, Ali Asghar Behroozpoor

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In this paper, we define an optimization problem corresponding to smooth and nonsmooth functions which its optimal solution is the first derivative of these functions in a domain. For this purpose, a linear programming problem corresponding to optimization problem is obtained. The optimal solution of this linear programming problem is the approximate generalized first derivative. In fact, we approximate generalized first derivative of nonsmooth functions as tailor series. We show the efficiency of our approach by some smooth and nonsmooth functions in some examples.

Keywords: general derivative, linear programming, optimization problem, smooth and nonsmooth functions

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Zicheng Wang

Abstract:

Offshore wind energy provides a huge potential for the expansion of renewable energies to the coastal countries. High demands are required concerning the shape and type of foundations for offshore wind turbines (OWTs) to find an economically, technically and environmentally-friendly optimal solution. A promising foundation concept is the hybrid foundation system, which consists of a steel plate attached to the outer side of a hollow steel pipe pile. In this study, the bearing behavior of a large diameter foundation is analyzed using a 3-dimensional finite element (FE) model. Non-linear plastic soil behavior is considered. The results of the numerical simulations are compared to highlight the priority of the hybrid foundation to the conventional monopile foundation.

Keywords: hybrid foundation system, mechanical parameters, plastic soil behaviors, numerical simulations

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Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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Authors: El H. Bouziani, H. A. Reguieg Yssaad

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The phytotoxicity of heavy metals can be expressed on roots and visible part of plants and is characterized by molecular and metabolic answers at various levels of organization of the whole plant. The present study was undertaken on two varieties of broad bean Vicia faba (Sidi Aïch and Super Aguadulce). The device was mounted on a substrate prepared by mixing sand, soil and compost, the substrate was artificially contaminated with three doses of lead nitrate [Pb(NO3)2] 0, 500 and 1000 ppm. Our objective is to follow the behavior of plant opposite the stress by evaluating the physiological parameters. The results reveal a reduction in the parameters of the productivity (chlorophyll and proteins production) with an increase in the osmoregulators (soluble sugars and proline).These results show that the production of broad bean is strongly modified by the disturbance of its internal physiology under lead exposure.

Keywords: broad bean, lead, stress, physiological parameters, phytotoxicity

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Authors: Minjeong Kim, Seungchul Lee, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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A trajectory of set-point of ventilation control systems plays an important role for efficient ventilation inside subway stations since it affects the level of indoor air pollutants and ventilation energy consumption. To maintain indoor air quality (IAQ) at a comfortable range with lower ventilation energy consumption, the optimal trajectory of the ventilation control system needs to be determined. The concentration of air pollutants inside the station shows a diurnal variation in accordance with the variations in the number of passengers and subway frequency. To consider the diurnal variation of IAQ, an iterative dynamic programming (IDP) that searches for a piecewise control policy by separating whole duration into several stages is used. When outdoor air is contaminated by pollutants, it enters the subway station through the ventilation system, which results in the deteriorated IAQ and adverse effects on passenger health. In this study, to consider the influence of outdoor air quality (OAQ), a new performance index of the IDP with the passenger health risk and OAQ is proposed. This study was carried out for an underground subway station at Seoul Metro, Korea. The optimal set-points of the ventilation control system are determined every 3 hours, then, the ventilation controller adjusts the ventilation fan speed according to the optimal set-point changes. Compared to manual ventilation system which is operated irrespective of the OAQ, the IDP-based ventilation control system saves 3.7% of the energy consumption. Compared to the fixed set-point controller which is operated irrespective of the IAQ diurnal variation, the IDP-based controller shows better performance with a 2% decrease in energy consumption, maintaining the comfortable IAQ range inside the station.

Keywords: indoor air quality, iterative dynamic algorithm, outdoor air information, ventilation control system

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Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

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Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

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Authors: Yongmin You

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Electric machines for office automation device such as printer and scanner have been required the low noise and vibration performance. Many researches about the low noise and vibration of polygon mirror scanner motor have been also progressed. The noise and vibration of polygon mirror scanner motor can be classified by aerodynamic, structural and electromagnetic. Electromagnetic noise and vibration can be occurred by high cogging torque and nonsinusoidal back EMF. To improve the cogging torque and back EMF characteristic, we apply unequal air-gap. To analyze characteristic of a polygon mirror scanner motor, two dimensional finite element method is used. To minimize the cogging torque of a polygon mirror motor, Kriging based on latin hypercube sampling (LHS) is utilized. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 23.4 % while maintaining the back EMF and average torque. To verify the optimal design results, the experiment was performed. We measured the vibration in motors at 23,600 rpm which is the rated velocity. The radial and axial gravitational acceleration of the optimal model were declined more than seven times and three times, respectively. From these results, a shape optimized unequal polygon mirror scanner motor has shown the usefulness of an improvement in the torque ripple and electromagnetic vibration characteristic.

Keywords: polygon mirror scanner motor, optimal design, finite element method, vibration

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

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The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: A. Graa, I. Ziane, F. Benhamida, S. Souag

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This paper presents a comparative analysis study of an efficient and reliable quadratic programming (QP) to solve economic load dispatch (ELD) problem with considering transmission losses in a power system. The proposed QP method takes care of different unit and system constraints to find optimal solution. To validate the effectiveness of the proposed QP solution, simulations have been performed using Algerian test system. Results obtained with the QP method have been compared with other existing relevant approaches available in literatures. Experimental results show a proficiency of the QP method over other existing techniques in terms of robustness and its optimal search.

Keywords: economic dispatch, quadratic programming, Algerian network, dynamic load

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Authors: Faisal Alshuwaier, Ali Areshey

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Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a concept graph generation mechanism, which is based on a text classification and optimal fuzzy relationship extraction. Furthermore, the work presented in this paper explains the application of fuzzy relationship extraction and branch and bound method to simplify the texts.

Keywords: extraction, max-prod, fuzzy relations, text mining, memberships, classification, memberships, classification

Procedia PDF Downloads 558

Authors: L. Vivet, L. Benabou, O. Simon

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With highly demanding applications in the field of power electronics, there is an increasing need to have interconnection materials with properties that can ensure both good mechanical assembly and high thermal/electrical conductivities. So far, lead-free solders have been considered an attractive solution, but recently, sintered joints based on nano-silver paste have been used for die attach and have proved to be a promising solution offering increased performances in high-temperature applications. In this work, the main parameters of the bonding process using silver oxalates are studied, i.e., the heating rate and the bonding pressure mainly. Their effects on both the mechanical and thermal properties of the sintered layer are evaluated following an experimental design. Pairs of copper substrates with gold metallization are assembled through the sintering process to realize the samples that are tested using a micro-traction machine. In addition, the obtained joints are examined through microscopy to identify the important microstructural features in relation to the measured properties. The formation of an intermetallic compound at the junction between the sintered silver layer and the gold metallization deposited on copper is also analyzed. Microscopy analysis exhibits a nanoporous structure of the sintered material. It is found that higher temperature and bonding pressure result in higher densification of the sintered material, with higher thermal conductivity of the joint but less mechanical flexibility to accommodate the thermo-mechanical stresses arising during service. The experimental design allows hence the determination of the optimal process parameters to reach sufficient thermal/mechanical properties for a given application. It is also found that the interphase formed between silver and gold metallization is the location where the fracture occurred after the mechanical testing, suggesting that the inter-diffusion mechanism between the different elements of the assembly leads to the formation of a relatively brittle compound.

Keywords: nanoporous structure, silver oxalate, sintering, mechanical strength, thermal conductivity, microelectronic packaging

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: M. H. Abedi, A. Jalilvand

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The economic development benefits of wind energy may be the most tangible basis for the local and state officials’ interests. In addition to the direct salaries associated with building and operating wind projects, the wind energy industry provides indirect jobs and benefits. The optimal planning of a wind farm is one most important topic in renewable energy technology. Many methods have been implemented to optimize the cost and output benefit of wind farms, but the contribution of this paper is mentioning different types of service providers and also time of installation of wind turbines during planning horizon years. Genetic algorithm (GA) is used to optimize the problem. It is observed that an appropriate layout of wind farm can cause to minimize the different types of cost.

Keywords: renewable energy, wind farm, optimization, planning

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

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Authors: Kooshina Koosha, Sima Habibi, Azam Talebian

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Electrospinning is a simple, versatile and widely accepted technique to produce ultra-fine fibers ranging from nanometer to micron. Recently there has been great interest in developing this technique to produce nanofibers with novel properties and functionalities. The electrospinning field is extremely broad, and consequently there have been many useful reviews discussing various aspects from detailed fiber formation mechanism to the formation of nanofibers and to discussion on a wide range of applications. On the other hand, the focus of this study is quite narrow, highlighting electrospinning parameters. This work will briefly cover the solution and processing parameters (for instance; concentration, solvent type, voltage, flow rate, distance between the collector and the tip of the needle) impacting the morphological characteristics of nanofibers, such as diameter. In this paper, a comprehensive work would be presented on the research of producing nanofibers from natural polymer entitled Gelatin.

Keywords: electrospinning, solution parameters, process parameters, natural fiber

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Authors: Chien-Chih Lin

Abstract:

This study argues that the optimal diversifications for the maximization of bank value are asymmetrical; they depend on the business cycle. During times of expansion, systematic risks are relatively low, and hence there is only a slight effect from raising them with a diversified portfolio. Consequently, the benefit of reducing individual risks dominates any loss from raising systematic risks, leading to a higher value for a bank by holding a diversified portfolio of assets. On the contrary, in times of recession, systematic risks are relatively high. It is more likely that the loss from raising systematic risks surpasses the benefit of reducing individual risks from portfolio diversification. Consequently, more diversification leads to lower bank values. Finally, some empirical evidence from the banks in Taiwan is provided.

Keywords: diversification, default probability, systemic risk, banking, business cycle

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Authors: İbrahim Hakkı Erkan, Özcan Tan

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The performance of jet grout columns was affected by many controlled and uncontrolled parameters. The leading parameters for the controlled ones can be listed as injection pressure, rod pulling speed, rod rotation speed, number of nozzles, nozzle diameter and Water/Cement ratio. And the uncontrolled parameters are soil type, soil structure, soil layering condition, underground water level, the changes in strength parameters and the rheologic properties of cement in time. In this study, the performance of jet grout columns and the effects of pulling speed and rotation speed were investigated experimentally. For this purpose, a laboratory type jet grouting system was designed for the experiments. Through this system, jet grout columns were produced in three different conditions. The results of the study showed that the grout pressure and the lifting speed significantly affect the performance of the jet grouting columns.

Keywords: jet grout, sandy soils, soil improvement, soilcreate

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Authors: Jaime E. Fernandez, Pablo J. Valverde

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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

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Authors: Serkan Aras, Emrah Gulay

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Combining various forecasting models is an important tool for researchers to attain more accurate forecasts. A great number of papers have shown that selecting single models as dissimilar models, or methods based on different information as possible leads to better forecasting performances. However, there is not a certain rule regarding the number of single models to be used in any combining methods. This study focuses on determining the optimal or near optimal number for single models with the help of statistical tests. An extensive experiment is carried out by utilizing some well-known time series data sets from diverse fields. Furthermore, many rival forecasting methods and some of the commonly used combining methods are employed. The obtained results indicate that some statistically significant performance differences can be found regarding the number of the single models in the combining methods under investigation.

Keywords: combined forecast, forecasting, M-competition, time series

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Authors: Y. Sefir, Z. Aziz, S. Cherid, Z. F. Meghoufel, F. Bendahama, S. Terkhi, B. Bouadjemi. A. Zitouni S. Bentata

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This work is to study the effect of the variation of structural parameters on the band structure in the quasiperiodic Fibonacci superlattices AlxGa1-xAs/GaAs using the formalism of the transfer matrix and Airy function. Our results show that increasing the width of Fibonacci’s wells of allows to the confinement of subminibands with a widening of minigaps, this causes a consistent and coherent fragmentation. The barrier thickness of Fibonacci bf acts on the width of subminibands by controlling the interaction force between neighboring eigenstates. Its increase gives rise to singularly extended states. The barrier height Fibonacci Vf permit to control the degree of structural disorder in these structures. The variation of these parameters permits the design of laser with modulated wavelength.

Keywords: transmission coefficient – Quasiperiodic superlattices- singularly localized and extended states- structural parameters- Laser with modulated wavelength

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

Procedia PDF Downloads 280