Search results for: grasshopper optimization algorithm

Authors: Carlos Caro, Ernest Blade, Nestor Rojas

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This study determined the relationship between basic geo-technical parameters and parameters of the hydro logical model Thomas for water balance of rural watersheds, as a methodological calibration application, applicable in distributed models as IBER model, which represents a distributed system simulation models for unsteady flow numerical free surface. There was an exploration in 25 points (on 15 sub) basin of Rio Piedras (Boy.) obtaining soil samples, to which geo-technical characterization was performed by laboratory tests. Thomas model has a physical characterization of the input area by only four parameters (a, b, c, d). Achieve measurable relationship between geo technical parameters and 4 values of hydro logical parameters helps to determine subsurface, underground and surface flow more agile manner. It is intended in this way to reach some solutions regarding limits initial model parameters on the basis of Thomas geo-technical characterization. In hydro geological models of rural watersheds, calibration is an important process in the characterization of the study area. This step can require a significant computational cost and time, especially if the initial values or parameters before calibration are outside of the geo-technical reality. A better approach in these initial values means optimization of these process through a geo-technical materials area, where is obtained an important approach to the study as in the starting range of variation for the calibration parameters.

Keywords: distributed hydrology, hydrological and geotechnical characterization, Iber model

Procedia PDF Downloads 522

Authors: H. Tounsadi, A. Khalidi, M. Abdennouri, N. Barka

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The objective of this study was to produce high quality activated carbons from Diplotaxis harra biomass by potassium hydroxide activation and their application for heavy metals removal. To reduce the number of experiments, full factorial experimental design at two levels were carried out to occur optimal preparation conditions and better conditions for the removal of cadmium and cobalt ions from aqueous solutions. The influence of different variables during the activation process, such as carbonization temperature, activation temperature, activation time and impregnation ratio (g KOH/g carbon) have been investigated, and the best production conditions were determined. The experimental results showed that removal of cadmium and cobalt ions onto activated carbons was more sensitive to methylene blue index instead of iodine number. Although, the removal of cadmium and cobalt ions is more influenced by activation temperature with a negative effect followed by the impregnation ratio with a positive impact. Based on the statistical data, the best conditions for the removal of cadmium and cobalt by prepared activated carbons have been established. The maximum iodine number and methylene blue index obtained under these conditions and the greater sorption capacities for cadmium and cobalt were investigated. These sorption capacities were greater than those of a commercial activated carbon used in water treatment.

Keywords: activated carbon, cadmium, cobalt, Diplotaxis harra, experimental design, potassium hydroxide

Procedia PDF Downloads 200

Authors: Yoftahe Nigussie

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This report presents a final year project pertaining to the design of Fire tube boiler for the purpose of producing saturated steam. The objective of the project is to produce saturated steam for different purpose with a capacity of 2000kg/h at 12bar design pressure by performing a design of a higher performance fire tube boiler that considered the requirements of cost minimization and parameters improvement. This is mostly done in selection of appropriate material for component parts, construction materials and production methods in different steps of analysis. In the analysis process, most of the design parameters are obtained by iterating with related formulas like selection of diameter of tubes with overall heat transfer coefficient optimization, and the other selections are also as like considered. The number of passes is two because of the size and area of the tubes and shell. As the analysis express by using heavy oil fuel no6 with a higher heating value of 44000kJ/kg and lower heating value of 41300kJ/kg and the amount of fuel consumed 140.37kg/hr. and produce 1610kw of heat with efficiency of 85.25%. The flow of the fluid is a cross flow because of its own advantage and the arrangement of the tube in-side the shell is welded with the tube sheet, and the tube sheet is attached with the shell and the end by using a gasket and weld. The design of the shell, using European Standard code section, is as like pressure vessel by considering the weight, including content and the supplementary accessories such as lifting lugs, openings, ends, man hole and supports with detail and assembly drawing.

Keywords: steam generation, external treatment, internal treatment, steam velocity

Procedia PDF Downloads 97

Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

Procedia PDF Downloads 301

Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

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Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

Procedia PDF Downloads 256

Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

Procedia PDF Downloads 270

Authors: A. M. Khourshid, A. M. El-Kassas, I. Sabry

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The objective of this work was to investigate the mechanical properties in order to demonstrate the feasibility of friction stir welding for joining Al 6061 aluminium alloys. Welding was performed on pipe with different thickness (2, 3 and 4 mm), five rotational speeds (485, 710, 910, 1120 and 1400 rpm) and a traverse speed of 4mm/min. This work focuses on two methods which are artificial neural networks using software and Response Surface Methodology (RSM) to predict the tensile strength, the percentage of elongation and hardness of friction stir welded 6061 aluminium alloy. An Artificial Neural Network (ANN) model was developed for the analysis of the friction stir welding parameters of 6061 pipe. Tensile strength, the percentage of elongation and hardness of weld joints were predicted by taking the parameters tool rotation speed, material thickness and axial force as a function. A comparison was made between measured and predicted data. Response Surface Methodology (RSM) was also developed and the values obtained for the response tensile strength, the percentage of elongation and hardness are compared with measured values. The effect of FSW process parameters on mechanical properties of 6061 aluminium alloy has been analysed in detail.

Keywords: friction stir welding, aluminium alloy, response surface methodology, artificial neural network

Procedia PDF Downloads 293

Authors: Ayoub Moufid, Najib Bennis, Soumia El Hani

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The objective of greenhouse climate control is to improve the culture development and to minimize the production costs. A greenhouse is an open system to external environment and the challenge is to regulate the internal climate despite the strong meteorological disturbances. The internal state of greenhouse considered in this work is defined by too relevant and coupled variables, namely inside temperature and hygrometry. These two variables are chosen to describe the internal state of greenhouses due to their importance in the development of plants and their sensitivity to external climatic conditions, sources of weather disturbances. A multivariable model is proposed and validated by considering a greenhouse as black-box system and the least square method is applied to parameters identification basing on collected experimental measures. To regulate the internal climate, we propose a Model Predictive Control (MPC) scheme. This one considers the measured meteorological disturbances and the physical and operational constraints on the control and state variables. A successful feasibility study of the proposed controller is presented, and simulation results show good performances despite the high interaction between internal and external variables and the strong external meteorological disturbances. The inside temperature and hygrometry are tracking nearly the desired trajectories. A comparison study with an On/Off control applied to the same greenhouse confirms the efficiency of the MPC approach to inside climate control.

Keywords: climate control, constraints, identification, greenhouse, model predictive control, optimization

Procedia PDF Downloads 206

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 196

Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

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The biodegradable family of polymers polyhydroxyalkanoates are interesting substitutes for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization

Procedia PDF Downloads 457

Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

Procedia PDF Downloads 150

Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

Procedia PDF Downloads 153

Authors: Ahmet Helvaci, Selcuk Dogan

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Reed in especially almost all the lakes in Western Anatolia grows naturally. Due to the abundance of reed, pyrolysis of reed is very economical and practical application. In this study, it is aimed to determine the optimum conditions for the pyrolysis of the reed which is a cheap and abundant raw material and to evaluate pyrolysis products. For this purpose, reed was used obtained from Eber Lake located in the borders of Bolvadin county of Afyonkarahisar. Optimum pyrolysis conditions have been determined by examining the effects of changes in pyrolysis temperature and pyrolysis time. The evaluation of the obtained liquid and solid pyrolysis products has been investigated. Especially evaluability of solid carbon black production of tires has been investigated. Tire samples were prepared with carbon black samples obtained as a result of the pyrolysis process at different temperatures. Then, performance tests were made and compared with reference carbon blacks, used in the market and standards. At the same time, surface area measurement analysis of carbon black samples was made and compared again with reference carbon blacks. In addition, the fuel values of liquid products were also determined by calorimeter. It has been determined that the best surface area (about 370 m²/g) for carbon black samples, for tire production is 40 minutes at 500ᵒC. It was also found that the best result for evaluation studies in tire production was carbon black samples obtained at 450ᵒC pyrolysis temperature. In addition, it was seen that the calorimetry results of the liquid product obtained during 60 minutes of pyrolysis were quite good (around 5500 kcal/kg).

Keywords: evaluation of products, optimization, pyrolysis, reed

Procedia PDF Downloads 193

Authors: Dinesh Pathaka, Tomas Wagnera, J. M. Nunzib

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We investigated blends of MdPVV.PCBM.AIS for photovoltaic application. AgInSe2 powder was synthesized by sealing and heating the stoichiometric constituents in evacuated quartz tube ampule. Fine grinded AIS powder was dispersed in MD-MOPVV and PCBM with and without surfactant. Different concentrations of these particles were suspended in the polymer solutions and spin casted onto ITO glass. Morphological studies have been performed by atomic force microscopy and optical microscopy. The blend layers were also investigated by various techniques like XRD, UV-VIS optical spectroscopy, AFM, PL, after a series of various optimizations with polymers/concentration/deposition/ suspension/surfactants etc. XRD investigation of blend layers shows clear evidence of AIS dispersion in polymers. Diode behavior and cell parameters also revealed it. Bulk heterojunction hybrid photovoltaic device Ag/MoO3/MdPVV.PCBM.AIS/ZnO/ITO was fabricated and tested with standard solar simulator and device characterization system. The best performance and photovoltaic parameters we obtained was an open-circuit voltage of about Voc 0.54 V and a photocurrent of Isc 117 micro A and an efficiency of 0.2 percent using a white light illumination intensity of 23 mW/cm2. Our results are encouraging for further research on the fourth generation inorganic organic hybrid bulk heterojunction photovoltaics for energy. More optimization with spinning rate/thickness/solvents/deposition rates for active layers etc. need to be explored for improved photovoltaic response of these bulk heterojunction devices.

Keywords: thin films, photovoltaic, hybrid systems, heterojunction

Procedia PDF Downloads 276

Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 205

Authors: Benkouiten Imene, Chabli Ouerdia, Boutoutaou Hamid, Kadri Nesrine, Bouledroua Omar

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Algeria is actively enhancing gas productivity by augmenting the supply flow. However, this effort has led to increased internal pressure, posing a potential risk to the pipeline's integrity, particularly in the presence of corrosion defects. Sonatrach relies on a vast network of pipelines spanning 24,000 kilometers for the transportation of gas and oil. The aging of these pipelines raises the likelihood of corrosion both internally and externally, heightening the risk of ruptures. To address this issue, a comprehensive inspection is imperative, utilizing specialized scraping tools. These advanced tools furnish a detailed assessment of all pipeline defects. It is essential to recalculate the pressure parameters to safeguard the corroded pipeline's integrity while ensuring the continuity of production. In this context, Sonatrach employs symbolic pressure limit calculations, such as ASME B31G (2009) and the modified ASME B31G (2012). The aim of this study is to perform a comparative analysis of various limit pressure calculation methods documented in the literature, namely DNV RP F-101, SHELL, P-CORRC, NETTO, and CSA Z662. This comparative assessment will be based on a dataset comprising 329 burst tests published in the literature. Ultimately, we intend to introduce a novel approach grounded in the finite element method, employing ANSYS software.

Keywords: pipeline burst pressure, burst test, corrosion defect, corroded pipeline, finite element method

Procedia PDF Downloads 58

Authors: T. Yu, L. Audibert, J. F. Chaix, D. Komatitsch, V. Garnier, J. M. Henault

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Linear Ultrasonic Techniques play a major role in Non-Destructive Evaluation (NDE) for civil engineering structures in concrete since they can meet operational requirements. Interpretation of ultrasonic measurements could be improved by a better understanding of ultrasonic wave propagation in a multiple scattering medium. This work aims to develop a 2D numerical model of ultrasonic wave propagation in a heterogeneous medium, like concrete, integrating the multiple scattering phenomena in SPECFEM software. The coherent field of multiple scattering is obtained by averaging numerical wave fields, and it is used to determine the effective phase velocity and attenuation corresponding to an equivalent homogeneous medium. First, this model is applied to one scattering element (a cylinder) in a homogenous medium in a linear-elastic system, and its validation is completed thanks to the comparison with analytical solution. Then, some cases of multiple scattering by a set of randomly located cylinders or polygons are simulated to perform parametric studies on the influence of frequency and scatterer size, concentration, and shape. Also, the effective properties are compared with the predictions of Waterman-Truell model to verify its validity. Finally, the mortar viscoelastic behavior is introduced in the simulation in order to considerer the dispersion and the attenuation due to porosity included in the cement paste. In the future, different steps will be developed: The comparisons with experimental results, the interpretation of NDE measurements, and the optimization of NDE parameters before an auscultation.

Keywords: attenuation, multiple-scattering medium, numerical modeling, phase velocity, ultrasonic measurements

Procedia PDF Downloads 275

Authors: Alime Cengiz, Talip Kahyaoglu

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Roasting process has the major importance to obtain desired aromatic taste of nuts. In this study, two kinds of roasting process were applied to hulled sesame seeds - vacuum oven and hot air roasting. Efficiency of Gene Expression Programming (GEP), a new soft computing technique of evolutionary algorithm that describes the cause and effect relationships in the data modelling system, and response surface methodology (RSM) were examined in the modelling of roasting processes over a range of temperature (120-180°C) for various times (30-60 min). Color attributes (L*, a*, b*, Browning Index (BI)), textural properties (hardness and fracturability) and moisture content were evaluated and modelled by RSM and GEP. The GEP-based formulations and RSM approach were compared with experimental results and evaluated according to correlation coefficients. The results showed that both GEP and RSM were found to be able to adequately learn the relation between roasting conditions and physical and textural parameters of roasted seeds. However, GEP had better prediction performance than the RSM with the high correlation coefficients (R2 >0.92) for the all quality parameters. This result indicates that the soft computing techniques have better capability for describing the physical changes occuring in sesame seeds during roasting process.

Keywords: genetic expression programming, response surface methodology, roasting, sesame seed

Procedia PDF Downloads 418

Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

Procedia PDF Downloads 502

Authors: Sepehr Lajevardi Esfahani, Shohre Rouhani, Zahra Ranjbar

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Graphene has gained much attention owing to its unique optical and electrical properties. Charge carriers in graphene sheets (GS) carry out a linear dispersion relation near the Fermi energy and behave as massless Dirac fermions resulting in unusual attributes such as the quantum Hall effect and ambipolar electric field effect. It also exhibits nondispersive transport characteristics with an extremely high electron mobility (15000 cm²/(Vs)) at room temperature. Recently, several progresses have been achieved in the fabrication of single- or multilayer GS for functional device applications in the fields of optoelectronic such as field-effect transistors ultrasensitive sensors and organic photovoltaic cells. In addition to device applications, graphene also can serve as reinforcement to enhance mechanical, thermal, or electrical properties of composite materials. Electrophoretic deposition (EPD) is an attractive method for development of various coatings and films. It readily applied to any powdered solid that forms a stable suspension. The deposition parameters were controlled in various thicknesses. In this study, the graphene electrodeposition conditions were optimized. The results were obtained from SEM, Ohm resistance measuring technique and AFM characteristic tests. The minimum sheet resistance of electrodeposited reduced graphene oxide layers is achieved at conditions of 2 V in 10 s and it is annealed at 200 °C for 1 minute.

Keywords: electrophoretic deposition (EPD), graphene oxide (GO), electrical conductivity, electro-optical devices

Procedia PDF Downloads 190

Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

Procedia PDF Downloads 448

Authors: Maryam Kalkatechi

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The paper presents the construction unit that was proposed as a result of researching and finding solutions for challenges of the traditional masonry unit. The concept of ‘unit as arrangements of cells’ was investigated in four categories of structure, handling and assembly, thermal characteristics and weather ability which resulted in construction unit as an independent system which shapes a part of the envelope. Comparing to the traditional wall systems in which the system is in layers, the part system is a monolithic piece by itself. Even though the overall wythe-10 inches- is less than the combined layers-14 inches- in a traditional wall system, it is still seen as a spatial component. The component as a furnishing of envelope is discussed from material application point of view. The algorithm definition of the arrangement cells crafts the relationship between cells and functionality with material. This craft is realized as the envelope furnishing. Three alternative materials in relation to furnishing the envelope are discussed for printing the construction unit; transparent plastic, opaque plastic and glass. The qualities vary in the four categories, however this paper focuses on the visual qualities of materials applied. In a diagram the qualities of the materials are compared in relation to each other.

Keywords: furnishing envelope, 3D printed construction unit, opaque plastic, transparent plastic, glass

Procedia PDF Downloads 181

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

Procedia PDF Downloads 355

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 389

Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

Procedia PDF Downloads 393

Authors: Y. L. Hor, H. S. Chu, V. P. Bui

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Composite material is widely used to replace conventional material, especially in the aerospace industry to reduce the weight of the devices. It is formed by combining reinforced materials together via adhesive bonding to produce a bulk material with alternated macroscopic properties. In bulk composites, degradation may occur in microscopic scale, which is in each individual reinforced fiber layer or especially in its matrix layer such as delamination, inclusion, disbond, void, cracks, and porosity. In this paper, we focus on the detection of defect in matrix layer which the adhesion between the composite plies is in contact but coupled through a weak bond. In fact, the adhesive defects are tested through various nondestructive methods. Among them, pulsed phase thermography (PPT) has shown some advantages providing improved sensitivity, large-area coverage, and high-speed testing. The aim of this work is to develop an efficient numerical model to study the application of PPT to the nondestructive inspection of weak bonding in composite material. The resulting thermal evolution field is comprised of internal reflections between the interfaces of defects and the specimen, and the important key-features of the defects presented in the material can be obtained from the investigation of the thermal evolution of the field distribution. Computational simulation of such inspections has allowed the improvement of the techniques to apply in various inspections, such as materials with high thermal conductivity and more complex structures.

Keywords: pulsed phase thermography, weak bond, composite, CFRP, computational modelling, optimization

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Authors: P. Jayashree, S. Rajkumar

Abstract:

With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Dawit Gebreegzabher Hagos, Yazezew Kebede Kiro, Mahmud Abdulkader, Henk H. D. F. Schallig, Dawit Wolday

Abstract:

Rapid and accurate visceral leishmaniasis (VL) diagnosis is needed to initiate prompt treatment to reduce morbidity and mortality. Here, we evaluated the performance of loop-mediated isothermal amplification (LAMP) assay for the diagnosis of VL from blood in an endemic area in Ethiopia. LAMP was positive in 117/122 confirmed VL cases and negative in 149/152 controls, resulting in a sensitivity of 95.9% (95% CI: 90.69–98.66) and a specificity of 98.0% (95% CI: 94.34–99.59), respectively. The sensitivity of the LAMP assay was 95.0% (95% CI: 88.61–98.34) in HIV-negatives and 100% (95% CI: 85.18–100.0) in HIV-positives. Compared with microscopy, LAMP detected 82/87 (94.3%, 95% CI: 87.10–98.11) of the microscopy1 cases and was negative in 11/27 (40.7%, 95% CI: 22.39–61.20) of the microscopy2 cases. Compared with the rK39 serology, LAMP detected 113/120 (94.2%, 95% CI: 88.35–97.62) of the rK391 cases and was negative in 149/154 (96.8%, 95% CI: 92.59–98.94) of the rK392 cases. However, when compared with microscopy only, rK39 detected 83/87 (95.4%, 95% CI: 88.64–98.73) of the microscopy1 cases and negative in only 12/27 (44.4%, 95% CI: 25.48–64.67) of the microscopy– cases. There was an excellent agreement between rK39 and LAMP (Kappa 5 0.91, 95% CI: 0.86–0.96). Furthermore, an algorithm using rK39 followed by LAMP would yield a sensitivity of 99.2% (95%CI: 95.52–99.89) and a specificity of 98.0% (95% CI: 94.34–99.59). The findings demonstrate that the LAMP assay is an accurate and rapid molecular assay for VL diagnosis, including in HIV-1 co-infected patients, in an endemic setting.

Keywords: visceral leishmaniasis, HIV, diagnosis, LAMP, Ethiopia

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

Abstract:

Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

Abstract:

The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

Procedia PDF Downloads 459