Search results for: distribution system and optimization

Authors: Elyas Palantei, Dewiani, Farid Armin, Ardiansyah

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High precision of printed microwave sensor utilized for sensing and monitoring the potential breast cancer existed in women breast tissue was optimally computed. The single element of UWB printed sensor that successfully modeled through several numerical optimizations was multiple fabricated and incorporated with woman bra to form the spherical sensors array. One sample of UWB microwave sensor obtained through the numerical computation and optimization was chosen to be fabricated. In overall, the spherical sensors array consists of twelve stair patch structures, and each element was individually measured to characterize its electrical properties, especially the return loss parameter. The comparison of S11 profiles of all UWB sensor elements is discussed. The constructed UWB sensor is well verified using HFSS programming, CST programming, and experimental measurement. Numerically, both HFSS and CST confirmed the potential operation bandwidth of UWB sensor is more or less 4.5 GHz. However, the measured bandwidth provided is about 1.2 GHz due to the technical difficulties existed during the manufacturing step. The configuration of UWB microwave sensing and monitoring system implemented consists of 12 element UWB printed sensors, vector network analyzer (VNA) to perform as the transceiver and signal processing part, the PC Desktop/Laptop acting as the image processing and displaying unit. In practice, all the reflected power collected from whole surface of artificial breast model are grouped into several numbers of pixel color classes positioned on the corresponding row and column (pixel number). The total number of power pixels applied in 2D-imaging process was specified to 100 pixels (or the power distribution pixels dimension 10x10). This was determined by considering the total area of breast phantom of average Asian women breast size and synchronizing with the single UWB sensor physical dimension. The interesting microwave imaging results were plotted and together with some technical problems arisen on developing the breast sensing and monitoring system are examined in the paper.

Keywords: UWB sensor, UWB microwave imaging, spherical array, breast cancer monitoring, 2D-medical imaging

Procedia PDF Downloads 189

Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

Procedia PDF Downloads 438

Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

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The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: fatigue life, finite element analysis, tolerance analysis, optimization

Procedia PDF Downloads 155

Authors: Seon Soon Choi

Abstract:

Magnesium alloy has been widely used in structure such as an automobile. It is necessary to consider probabilistic characteristics of a structural material because a fatigue behavior of a structure has a randomness and uncertainty. The purpose of this study is to find the characteristics of the cumulative distribution function (CDF) of the grown crack size at a specified fatigue crack propagation life and to investigate a statistical crack propagation in magnesium alloys. The statistical fatigue data of the grown crack size are obtained through the fatigue crack propagation (FCP) tests under different maximum fatigue load conditions conducted on the replicated specimens of magnesium alloys. The 3-parameter Weibull distribution is used to find the CDF of grown crack size. The CDF of grown crack size in case of larger maximum fatigue load has longer tail in below 10 percent and above 90 percent. The fatigue failure occurs easily as the tail of CDF of grown crack size becomes long. The fatigue behavior under the larger maximum fatigue load condition shows more rapid propagation and failure mode.

Keywords: cumulative distribution function, fatigue crack propagation, grown crack size, magnesium alloys, maximum fatigue load

Procedia PDF Downloads 283

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

Procedia PDF Downloads 358

Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

Procedia PDF Downloads 132

Authors: Asma Shaheen Hashmi, Omer Riaz, Khalid Mahmood, Fahad Ullah, Tanveer Ahmad

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The urban landscapes are being change with the population growth and advancements in new technologies. The urban sprawl pattern and utilizes are related to the local socioeconomic and physical condition. Urban policy decisions are executed mostly through spatial planning. A decision support system (DSS) is very powerful tool which provides flexible knowledge base method for urban planning. An application was developed using geographical information system (GIS) for urban planning. A scenario based DSS was developed to integrate the hierarchical muti-criteria data of different aspects of urban landscape. These were physical environment, the dumping site, spatial distribution of road network, gas and water supply lines, and urban watershed management, selection criteria for new residential, recreational, commercial and industrial sites. The model provided a framework to incorporate the sustainable future development. The data can be entered dynamically by planners according to the appropriate criteria for the management of urban landscapes.

Keywords: urban, GIS, spatial, criteria

Procedia PDF Downloads 632

Authors: A. A. Dare, E. U. Iniegbedion

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Industrial furnaces generally involve enclosures of fire typically initiated by the combustion of gases. The fire leads to temperature distribution inside the enclosure. A proper understanding of the temperature and velocity distribution within the enclosure is often required for optimal design and use of the furnace. This study was therefore directed at numerical modeling of temperature distribution inside an enclosure as typical in a furnace. A mathematical model was developed from the conservation of mass, momentum and energy. The stream function-vorticity formulation of the governing equations was solved by an alternating direction implicit (ADI) finite difference technique. The finite difference formulation obtained were then developed into a computer code. This was used to determine the temperature, velocities, stream function and vorticity. The effect of the wall heat conduction was also considered, by assuming a one-dimensional heat flow through the wall. The computer code (MATLAB program) developed was used for the determination of the aforementioned variables. The results obtained showed that the transient temperature distribution assumed a uniform profile which becomes more chaotic with increasing time. The vertical velocity showed increasing turbulent behavior with time, while the horizontal velocity assumed decreasing laminar behavior with time. All of these behaviours were equally reported in the literature. The developed model has provided understanding of heat transfer process in an industrial furnace.

Keywords: heat source, modelling, enclosure, furnace

Procedia PDF Downloads 251

Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: accommodation establishments, human resource management, multi-objective optimization on the basis of ratio analysis, multi-criteria decision making, step-wise weight assessment ratio analysis

Procedia PDF Downloads 339

Authors: M. Bounechada, M. Fenni, S. Bouharati, S. E. Doumandji

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The study was taken in Setif region (36° 11' 29 N and 5° 24' 34 E) located at the north-eastern of Algeria. This paper recorded and discusses zoogeography and host plant relationships of Setifian species Alticinae subfamily. A total of 50 species belonging to Alticinae subfamily of Chrysomelidae which is the economically important familty, were recorded from differentes localities of Setif region. They are included in 10 genera. Genera Longitarsus Berthold, 1827 is less species-rich than the other Alticinae genera captured. It represens about 38% of the all species collected. Cruciferae and Compositae were the mostly prefered host plant families representing Alticinae species. For each species we mentioned the collecting sites, geographical distribution and the host plants.

Keywords: Algeria, Alticinae, Chrysomelidae, Coleoptera, distribution, host plants, species composition, Setif

Procedia PDF Downloads 232

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 287

Authors: Fares Senouci, Bachir Imine

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This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

Procedia PDF Downloads 248

Authors: Walid Moudani

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The Crew Reserve Assignment Problem (CRAP) considers the assignment of the crew members to a set of reserve activities covering all the scheduled flights in order to ensure a continuous plan so that operations costs are minimized while its solution must meet hard constraints resulting from the safety regulations of Civil Aviation as well as from the airlines internal agreements. The problem considered in this study is of highest interest for airlines and may have important consequences on the service quality and on the economic return of the operations. In this communication, a new mathematical formulation for the CRAP is proposed which takes into account the regulations and the internal agreements. While current solutions make use of Artificial Intelligence techniques run on main frame computers, a low cost approach is proposed to provide on-line efficient solutions to face perturbed operating conditions. The proposed solution method uses a dynamic programming approach for the duties scheduling problem and when applied to the case of a medium airline while providing efficient solutions, shows good potential acceptability by the operations staff. This optimization scheme can then be considered as the core of an on-line Decision Support System for crew reserve assignment operations management.

Keywords: airlines operations management, combinatorial optimization, dynamic programming, crew scheduling

Procedia PDF Downloads 351

Authors: Nazanin Ahmadi Daryakenari

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Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

Procedia PDF Downloads 86

Authors: Geun-Yeon Kim, S. P. Praveen Kumar, Kwon-Hee Lee

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A steering knuckle arm is the component that connects the steering system and suspension system. The structural performances such as stiffness, strength, and durability are considered in its design process. The former study suggested the lightweight design of a knuckle arm considering the structural performances and using the metamodel-based optimization. The six shape design variables were defined, and the optimum design was calculated by applying the kriging interpolation method. The finite element method was utilized to predict the structural responses. The suggested knuckle was made of the aluminum Al6082, and its weight was reduced about 60% in comparison with the base steel knuckle, satisfying the design requirements. Then, we investigated its manufacturability by performing foraging analysis. The forging was done as hot process, and the product was made through two-step forging. As a final step of its developing process, the durability is investigated by using the flexible dynamic analysis software, LS-DYNA and the pre and post processor, eta/VPG. Generally, a car make does not provide all the information with the part manufacturer. Thus, the part manufacturer has a limit in predicting the durability performance with the unit of full car. The eta/VPG has the libraries of suspension, tire, and road, which are commonly used parts. That makes a full car modeling. First, the full car is modeled by referencing the following information; Overall Length: 3,595mm, Overall Width: 1,595mm, CVW (Curve Vehicle Weight): 910kg, Front Suspension: MacPherson Strut, Rear Suspension: Torsion Beam Axle, Tire: 235/65R17. Second, the road is selected as the cobblestone. The road condition of the cobblestone is almost 10 times more severe than that of usual paved road. Third, the dynamic finite element analysis using the LS-DYNA is performed to predict the durability performance of the suggested knuckle arm. The life of the suggested knuckle arm is calculated as 350,000km, which satisfies the design requirement set up by the part manufacturer. In this study, the overall design process of a knuckle arm is suggested, and it can be seen that the developed knuckle arm satisfies the design requirement of the durability with the unit of full car. The VPG analysis is successfully performed even though it does not an exact prediction since the full car model is very rough one. Thus, this approach can be used effectively when the detail to full car is not given.

Keywords: knuckle arm, structural optimization, Metamodel, forging, durability, VPG (Virtual Proving Ground)

Procedia PDF Downloads 414

Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

Procedia PDF Downloads 137

Authors: Sen Yung Lee, Chih Cheng Huang, Te Wen Tu

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A solution methodology without using integral transformation is proposed to develop analytical solutions for transient heat conduction in nonuniform hollow cylinders with time-dependent boundary condition at the outer surface. It is shown that if the thermal conductivity and the specific heat of the medium are in arbitrary polynomial function forms, the closed solutions of the system can be developed. The influence of physical properties on the temperature distribution of the system is studied. A numerical example is given to illustrate the efficiency and the accuracy of the solution methodology.

Keywords: analytical solution, nonuniform hollow cylinder, time-dependent boundary condition, transient heat conduction

Procedia PDF Downloads 498

Authors: Goutom K. Pall

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At the very heart of the power system, power transmission (PT) acts as an essential link between power generation and distribution. Timely completion of PT infrastructures is therefore crucial to support the development of power system as a whole. Yet despite the importance, studies on PT infrastructure development projects are embryonic and, hence, PT projects undergoing widespread delays worldwide. These delay factors are idiosyncratic and identifying the critical delay factors is essential if the PT industry professionals are to complete their projects efficiently and within the expected timeframes. This study identifies and categorizes 46 causes of PT project delay under ten major groups using six sector expert’s recommendations studied by a preliminary questionnaire survey. Based on the experts’ strong recommendations, two new groups are introduced in the final questionnaire survey: sector specific factors (SSF) and general factors (GF). SSF pertain to delay factors applicable only to the PT projects, while GF represents less biased samples with shared responsibilities of all project parties involved in a project. The study then uses 112 data samples from the contractors to rank the delay factors using relative importance index (RII). The results reveal that SSF, GF and external factors are the most critical groups, while the highest ranked delay factors include the right of way (RoW) problems of transmission lines (TL), delay in payments, frequent changes in TL routes, poor communication and coordination among the project parties and accessibility to TL tower locations. Finally, recommendations are made to minimize the identified delay. The findings are expected to be of substantial benefit to professionals in minimizing time overrun in PT projects implementation, as well as power generation, power distribution, and non-power linear construction projects worldwide.

Keywords: delay, project delay, power transmission projects, time-overruns

Procedia PDF Downloads 174

Authors: Hadjadj Naima, K. Mahdi, D. Belhachat, F. S. Ait Chaouche, A. Ferradji

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The Nigella Sativa oil yield extracted by hydraulic pressing is influenced by the pressure temperature and size particles. The optimization of oil extraction is investigated. The rate of extraction of the whole seeds is very weak, a crushing of seeds is necessary to facilitate the extraction. This rate augments with the rise of the temperature and the pressure, and decrease of size particles. The best output (66%) is obtained for a granulometry lower than 1mm, a temperature of 50°C and a pressure of 120 bars.

Keywords: oil, Nigella sativa, extraction, optimization, temperature, pressure

Procedia PDF Downloads 473

Authors: J. Thiele

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Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

Procedia PDF Downloads 119

Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

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This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

Procedia PDF Downloads 550

Authors: Johnson Joseph Kwabina Arhinful, Owusu-Ansah Emmanuel Degraft Johnson, Okyere Gabrial Asare, Adebanji Atinuke Olusola

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This paper proposes a model to describe the blood types distribution of new Coronavirus (COVID-19) cases using the Bayesian Poisson - Hidden Markov Model (BP-HMM). With the help of the Gibbs sampler algorithm, using OpenBugs, the study first identifies the number of hidden states fitting European (EU) and African (AF) data sets of COVID-19 cases by blood type frequency. The study then compares the state-dependent mean of infection within and across the two geographical areas. The study findings show that the number of hidden states and infection rates within and across the two geographical areas differ according to blood type.

Keywords: BP-HMM, COVID-19, blood types, GIBBS sampler

Procedia PDF Downloads 126

Authors: Song Zhang, Hui Wang, Johannes Henrich Schleifenbaum

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Due to the increasing demand for quality assurance and reliability for additive manufacturing, the development of an advanced in-situ monitoring system is required to monitor the process anomalies as input for further process control. Optical-based monitoring systems, such as CMOS cameras and NIR cameras, are proved as effective ways to monitor the geometrical distortion and exceptional thermal distribution. Therefore, many studies and applications are focusing on the availability of the optical-based monitoring system for detecting varied types of defects. However, the capability of the monitoring setup is not quantified. In this study, a quantification model to evaluate the capability of the monitoring setups for the LPBF machine based on acquired monitoring data of a designed test artifact is presented, while the design of the relevant test artifacts is discussed. The monitoring setup is evaluated based on its hardware properties, location of the integration, and light condition. Methodology of data processing to quantify the capacity for each aspect is discussed. The minimal capability of the detectable size of the monitoring set up in the application is estimated by quantifying its resolution and accuracy. The quantification model is validated using a CCD camera-based monitoring system for LPBF machines in the laboratory with different setups. The result shows the model to quantify the monitoring system's performance, which makes the evaluation of monitoring systems with the same concept but different setups possible for the LPBF process and provides the direction to improve the setups.

Keywords: data processing, in-situ monitoring, LPBF process, optical system, quantization model, test artifact

Procedia PDF Downloads 194

Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

Procedia PDF Downloads 400

Authors: Maria De Los Angeles Ortega, Denis Bruneau, Patrick Sebastian, Jean-Pierre Nadeau, Alain Sommier, Saed Raji

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Phase change materials (PCM) present attractive features that made them a passive solution for thermal comfort assessment in buildings during summer time. They show a large storage capacity per volume unit in comparison with other structural materials like bricks or concrete. If their use is matched with the peak load periods, they can contribute to the reduction of the primary energy consumption related to cooling applications. Despite these promising characteristics, they present some drawbacks. Commercial PCMs, as paraffines, offer a low thermal conductivity affecting the overall performance of the system. In some cases, the material can be enhanced, adding other elements that improve the conductivity, but in general, a design of the unit that optimizes the thermal performance is sought. The material selection is the departing point during the designing stage, and it does not leave plenty of room for optimization. The PCM melting point depends highly on the atmospheric characteristics of the building location. The selection must relay within the maximum, and the minimum temperature reached during the day. The geometry of the PCM container and the geometrical distribution of these containers are designing parameters, as well. They significantly affect the heat transfer, and therefore its phenomena must be studied exhaustively. During its lifetime, an air-PCM unit in a building must cool down the place during daytime, while the melting of the PCM occurs. At night, the PCM must be regenerated to be ready for next uses. When the system is not in service, a minimal amount of thermal exchanges is desired. The aforementioned functions result in the presence of sensible and latent heat storage and release. Hence different types of mechanisms drive the heat transfer phenomena. An experimental test was designed to study the heat transfer phenomena occurring in a circular tube bundle air-PCM exchanger. An in-line arrangement was selected as the geometrical distribution of the containers. With the aim of visual identification, the containers material and a section of the test bench were transparent. Some instruments were placed on the bench for measuring temperature and velocity. The PCM properties were also available through differential scanning calorimeter (DSC) tests. An evolution of the temperature during both cycles, melting and solidification were obtained. The results showed some phenomena at a local level (tubes) and on an overall level (exchanger). Conduction and convection appeared as the main heat transfer mechanisms. From these results, two approaches to analyze the heat transfer were followed. The first approach described the phenomena in a single tube as a series of thermal resistances, where a pure conduction controlled heat transfer was assumed in the PCM. For the second approach, the temperature measurements were used to find some significant dimensionless numbers and parameters as Stefan, Fourier and Rayleigh numbers, and the melting fraction. These approaches allowed us to identify the heat transfer phenomena during both cycles. The presence of natural convection during melting might have been stated from the influence of the Rayleigh number on the correlations obtained.

Keywords: phase change materials, air-PCM exchangers, convection, conduction

Procedia PDF Downloads 169

Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola

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In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.

Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity

Procedia PDF Downloads 304

Authors: Chao-Ton Su, Li-Fei Chen

Abstract:

The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Jaeseung Lee, Muhammad Faizan Chinannai, Mohamed Hassan Gundu, Hyunchul Ju

Abstract:

In this paper, we numerically investigated the effect of metal foams on a real scale 242.57cm2 (19.1 cm × 12.7 cm) polymer electrolyte membrane fuel cell (PEFCs) using a three-dimensional two-phase PEFC model to substantiate design approach for PEFCs using metal foam as the flow distributor. The simulations were conducted under the practical low humidity hydrogen, and air gases conditions in order to observe the detailed operation result in the PEFCs using the serpentine flow channel in the anode and metal foam design in the cathode. The three-dimensional contours of flow distribution in the channel, current density distribution in the membrane and hydrogen and oxygen concentration distribution are provided. The simulation results revealed that the use of highly porous and permeable metal foam can be beneficial to achieve a more uniform current density distribution and better hydration in the membrane under low inlet humidity conditions. This study offers basic directions to design channel for optimal water management of PEFCs.

Keywords: polymer electrolyte fuel cells, metal foam, real-scale, numerical model

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Authors: Audrey Ngambia, Ondrej Masek, Valentina Erastova

Abstract:

Biochar is an amorphous carbon-rich material generated from the pyrolysis of biomass with multifarious properties and functionality. Biochar has shown proven applications in the treatment of flue gas and organic and inorganic pollutants in soil and water/wastewater as a result of its multiple surface functional groups and porous structures. These properties have also shown potential in energy storage and carbon capture. The availability of diverse sources of biomass to produce biochar has increased interest in it as a sustainable and environmentally friendly material. The properties and porous structures of biochar vary depending on the type of biomass and high heat treatment temperature (HHT). Biochars produced at HHT between 400°C – 800°C generally have lower H/C and O/C ratios, higher porosities, larger pore sizes and higher surface areas with temperature. While all is known experimentally, there is little knowledge on the porous role structure and functional groups play on processes occurring at the atomistic scale, which are extremely important for the optimization of biochar for application, especially in the adsorption of gases. Atomistic simulations methods have shown the potential to generate such amorphous materials; however, most of the models available are composed of only carbon atoms or graphitic sheets, which are very dense or with simple slit pores, all of which ignore the important role of heteroatoms such as O, N, S and pore morphologies. Hence, developing realistic models that integrate these parameters are important to understand their role in governing adsorption mechanisms that will aid in guiding the design and optimization of biochar materials for target applications. In this work, molecular dynamics simulations in the isobaric ensemble are used to generate realistic biochar models taking into account experimentally determined H/C, O/C, N/C, aromaticity, micropore size range, micropore volumes and true densities of biochars. A pore generation approach was developed using virtual atoms, which is a Lennard-Jones sphere of varying van der Waals radius and softness. Its interaction via a soft-core potential with the biochar matrix allows the creation of pores with rough surfaces while varying the van der Waals radius parameters gives control to the pore-size distribution. We focused on microporosity, creating average pore sizes of 0.5 - 2 nm in diameter and pore volumes in the range of 0.05 – 1 cm3/g, which corresponds to experimental gas adsorption micropore sizes of amorphous porous biochars. Realistic biochar models with surface functionalities, micropore size distribution and pore morphologies were developed, and they could aid in the study of adsorption processes in confined micropores.

Keywords: biochar, heteroatoms, micropore size, molecular dynamics simulations, surface functional groups, virtual atoms

Procedia PDF Downloads 66