Search results for: finite time convergence

Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

Procedia PDF Downloads 417

Authors: Anusuya Ghosh, Vishnu Narayanan

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The approximation of convex set by semidefinite representable set plays an important role in semidefinite programming, especially in modern convex optimization. To optimize a linear function over a convex set is a hard problem. But optimizing the linear function over the semidefinite representable set which approximates the convex set is easy to solve as there exists numerous efficient algorithms to solve semidefinite programming problems. So, our approximation technique is significant in optimization. We develop a technique to approximate any closed convex set, say K by compactly semidefinite representable set. Further we prove that there exists a sequence of compactly semidefinite representable sets which give tighter approximation of the closed convex set, K gradually. We discuss about the convergence of the sequence of compactly semidefinite representable sets to closed convex set K. The recession cone of K and the recession cone of the compactly semidefinite representable set are equal. So, we say that the sequence of compactly semidefinite representable sets converge strongly to the closed convex set. Thus, this approximation technique is very useful development in semidefinite programming.

Keywords: semidefinite programming, semidefinite representable set, compactly semidefinite representable set, approximation

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Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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Authors: Jared R. Chapman

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This study introduces a type of motivational information system called an educational engagement information system (EEIS). An EEIS draws on principles of behavioral economics, motivation theory, and learning cognition theory to design information systems that help students want to improve their performance. This study compares academic outcomes for course sections taught by part- and full-time instructors both with and without an EEIS. Without an EEIS, students in the part-time instructor's course sections demonstrated significantly higher failure rates (a 143.8% increase) and dropout rates (a 110.4% increase) with significantly fewer students scoring a B- or higher (39.8% decrease) when compared to students in the course sections taught by a full-time instructor. It is concerning that students in the part-time instructor’s course without an EEIS had significantly lower academic outcomes, suggesting less understanding of the course content. This could impact retention and continuation in a major. With an EEIS, when comparing part- and full-time instructors, there was no significant difference in failure and dropout rates or in the number of students scoring a B- or higher in the course. In fact, with an EEIS, the failure and dropout rates were statistically identical for part- and full-time instructor courses. When using an EEIS (compared with not using an EEIS), the part-time instructor showed a 62.1% decrease in failures, a 61.4% decrease in dropouts, and a 41.7% increase in the number of students scoring a B- or higher in the course. We are unaware of other interventions that yield such large improvements in academic performance. This suggests that using an EEIS such as Delphinium may compensate for part-time instructors’ limitations of expertise, time, or rewards that can have a negative impact on students’ academic outcomes. The EEIS had only a minimal impact on failure rates (7.7% decrease) and dropout rates (18.8% decrease) for the full-time instructor. This suggests there is a ceiling effect for the improvements that an EEIS can make in student performance. This may be because experienced instructors are already doing the kinds of things that an EEIS does, such as motivating students, tracking grades, and providing feedback about progress. Additionally, full-time instructors have more time to dedicate to students outside of class than part-time instructors and more rewards for doing so. Using adjunct and other types of part-time instructors will likely remain a prevalent practice in higher education management courses. Given that using part-time instructors can have a negative impact on student graduation and persistence in a field of study, it is important to identify ways we can augment part-time instructors’ performance. We demonstrated that when part-time instructors use an EEIS, it can result in significantly lower students’ failure and dropout rates and an increase in the rate of students earning a B- or above; and bring their students’ performance to parity with the performance of students taught by a full-time instructor.

Keywords: gamification, engagement, motivation, academic outcomes

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Authors: Jing Qingfeng, Wu Jiajia

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Due to the crowded orbits and shortage of frequency resources, utilizing of MIMO technology to improve spectrum efficiency and increase the capacity has become a necessary trend of broadband satellite communication. We analyze the main influenced factors and compare the BER performance of space-time block code (STBC) scheme and space-time trellis code (STTC) scheme. This paper emphatically studies the bit error rate (BER) performance of STTC and STBC under Rayleigh channel. The main emphasis is placed on the effects of the factors, such as terminal environment and elevation angles, on the BER performance of STBC and STTC schemes. Simulation results indicate that performance of STTC under Rayleigh channel is obviously improved with the increasing of transmitting and receiving antennas numbers, but the encoder state has little impact on the performance. Under Rayleigh channel, performance of Alamouti code is better than that of STTC.

Keywords: MIMO, space time block code (STBC), space time trellis code (STTC), Rayleigh channel

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Authors: A. Oukaira, A. Lakhssassi, O. Ettahri

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To make a good thermal management in an ABDM (Adapter Board Detector Module) card, we must first control temperature and its gradient from the first step in the design of integrated circuits ASIC of our complex system. In this paper, our main goal is to develop and validate the thermal stability in order to get an idea of the flow of heat around the ASIC in transient and thus address the thermal issues for integrated circuits at the ABDM card. However, we need heat sources simulations for ABDM card to establish its thermal mapping. This led us to perform simulations at each ASIC that will allow us to understand the thermal ABDM map and find real solutions for each one of our complex system that contains 36 ABDM map, taking into account the different layers around ASIC. To do a transient simulation under NISA, we had to build a function of power modulation in time TIMEAMP. The maximum power generated in the ASIC is 0.6 W. We divided the power uniformly in the volume of the ASIC. This power was applied for 5 seconds to visualize the evolution and distribution of heat around the ASIC. The DBC (Dirichlet Boundary conditions) method was applied around the ABDM at 25°C and just after these simulations in NISA tool we will validate them by COMSOL tool, wich is a numerical calculation software for a modular finite element for modeling a wide variety of physical phenomena characterizing a real problem. It will also be a design tool with its ability to handle 3D geometries for complex systems.

Keywords: ABDM, APD, thermal mapping, complex system

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Authors: Wei Xu, Abdo S. Haidar, Jianxin Gao

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Prosthetic socket is a component that connects the residual limb of an amputee with an artificial prosthesis. It is widely recognized as the most critical component that determines the comfort of a patient when wearing the prosthesis in his/her daily activities. Through the socket, the body weight and its associated dynamic load are distributed and transmitted to the prosthesis during walking, running or climbing. In order to achieve a good-fit socket for an individual amputee, it is essential to obtain the biomechanical properties of the residual limb. In current clinical practices, this is achieved by a touch-and-feel approach which is highly subjective. Although there have been significant advancements in prosthetic technologies such as microprocessor controlled knee and ankle joints in the last decade, the progress in designing a comfortable socket has been rather limited. This means that the current process of socket design is still very time-consuming, and highly dependent on the expertise of the prosthetist. Supported by the state-of-the-art sensor technologies and numerical simulations, a new socket design system is being developed to help prosthetists achieve rapid design of comfortable sockets for above knee amputees. This paper reports the research work related to establishing biomechanical models for socket design. Through numerical simulation using finite element method, comprehensive relationships between pressure on residual limb and socket geometry were established. This allowed local topological adjustment for the socket so as to optimize the pressure distributions across the residual limb. When the full body weight of a patient is exerted on the residual limb, high pressures and shear forces between the residual limb and the socket occur. During numerical simulations, various hyperplastic models, namely Ogden, Yeoh and Mooney-Rivlin, were used, and their effectiveness in representing the biomechanical properties of soft tissues of the residual limb was evaluated. This also involved reverse engineering, which resulted in an optimal representative model under compression test. To validate the simulation results, a range of silicone models were fabricated. They were tested by an indentation device which yielded the force-displacement relationships. Comparisons of results obtained from FEA simulations and experimental tests showed that the Ogden model did not fit well the soft tissue material indentation data, while the Yeoh model gave the best representation of the soft tissue mechanical behavior under indentation. Compared with hyperplastic model, the result showed that elastic model also had significant errors. In addition, normal and shear stress distributions on the surface of the soft tissue model were obtained. The effect of friction in compression testing and the influence of soft tissue stiffness and testing boundary conditions were also analyzed. All these have contributed to the overall goal of designing a good-fit socket for individual above knee amputees.

Keywords: above knee amputee, finite element simulation, hyperplastic model, prosthetic socket

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Khaled Suleiman Mohammed Al-Mashrafi

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A compositional plume is a fluid flow in a directional channel of finite width in another fluid of different material composition. The study of the dynamics of compositional plumes plays an essential role in many real-life applications like industrial applications (e.g., iron casting), environmental applications (e.g., salt fingers and sea ice), and geophysical applications (e.g., solidification at the inner core boundary (ICB) of the Earth, and mantle plumes). The dynamics of compositional plumes have been investigated experimentally and theoretically. The experimental works observed that the plume flow seems to be stable, although some experiments showed that it can be unstable. At the same time, the theoretical investigations showed that the plume flow is unstable. This is found to be true even if the plume is subject to rotation or/and in the presence of a magnetic field and even if another plume of different composition is also present. It is noticeable that all the theoretical studies on the dynamics of compositional plumes are conducted in unbounded domains. The present work is to investigate theoretically the influence of vertical walls (boundaries) on the dynamics of compositional plumes in the absence/presence of a rotation field. The mathematical model of the dynamics of compositional plumes used the equations of continuity, motion, heat, concentration of light material, and state. It is found that the presence of boundaries has a strong influence on the basic state solution as well as the stability of the plume, particularly when the plume is close to the boundary, but the compositional plume remains unstable.

Keywords: compositional plumes, stability, bounded domain, vertical boundaries

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Authors: Serge Provost, Abdous Saboor

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A q-analogue of the generalized extreme value distribution which includes the Gumbel distribution is introduced. The additional parameter q allows for increased modeling flexibility. The resulting distribution can have a finite, semi-infinite or infinite support. It can also produce several types of hazard rate functions. The model parameters are determined by making use of the method of maximum likelihood. It will be shown that it compares favourably to three related distributions in connection with the modeling of a certain hydrological data set.

Keywords: extreme value theory, generalized extreme value distribution, goodness-of-fit statistics, Gumbel distribution

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Authors: O. Bendermel, C. Seladji, M. Khaouani

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In this work, we made a numerical study of the thermal and dynamic behaviour of air in a horizontal channel with electronic components. The influence to use baffles on the profiles of velocity and temperature is discussed. The finite volume method and the algorithm Simple are used for solving the equations of conservation of mass, momentum and energy. The results found show that baffles improve heat transfer between the cooling air and electronic components. The velocity will increase from 3 times per rapport of the initial velocity.

Keywords: electronic components, baffles, cooling, fluids engineering

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

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Authors: S. Zhang, L. Zhang, X. Chen

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Due to the large uncertainty on the mechanical properties of FRP (fibre reinforced plastic), the reliability evaluation of FRP structures are currently receiving much attention in industry. However, possible statistical correlation between ply mechanical properties has been so far overlooked, and they are mostly assumed to be independent random variables. In this study, the statistical correlation between ply mechanical properties of uni-directional and plain weave composite is firstly analyzed by a combination of Monte-Carlo simulation and finite element modeling of the FRP unit cell. Large linear correlation coefficients between the in-plane mechanical properties are observed, and the correlation coefficients are heavily dependent on the uncertainty of the fibre volume ratio. It is also observed that the correlation coefficients related to Poisson’s ratio are negative while others are positive. To experimentally achieve the statistical correlation coefficients between in-plane mechanical properties of FRP, all concerned in-plane mechanical properties of the same specimen needs to be known. In-plane shear modulus of FRP is experimentally derived by the approach suggested in the ASTM standard D5379M. Tensile tests are conducted using the same specimens used for the shear test, and due to non-uniform tensile deformation a modification factor is derived by a finite element modeling. Digital image correlation is adopted to characterize the specimen non-uniform deformation. The preliminary experimental results show a good agreement with the numerical analysis on the statistical correlation. Then, failure probability of laminate plates is calculated in cases considering and not considering the statistical correlation, using the Monte-Carlo and Markov Chain Monte-Carlo methods, respectively. The results highlight the importance of accounting for the statistical correlation between ply mechanical properties to achieve accurate failure probability of laminate plates. Furthermore, it is found that for the multi-layer laminate plate, the statistical correlation between the ply elastic properties significantly affects the laminate reliability while the effect of statistical correlation between the ply strength is minimal.

Keywords: failure probability, FRP, reliability, statistical correlation

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

Procedia PDF Downloads 118

Authors: Neslihan Genckal, Reha Gursoy, Vedat Z. Dogan

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In this study, dynamic responses of composite plates on elastic foundations subjected to impact and moving loads are investigated. The first order shear deformation (FSDT) theory is used for moderately thick plates. Pasternak-type (two-parameter) elastic foundation is assumed. Elastic foundation effects are integrated into the governing equations. It is assumed that plate is first hit by a mass as an impact type loading then the mass continues to move on the composite plate as a distributed moving loading, which resembles the aircraft landing on airport pavements. Impact and moving loadings are modeled by a mass-spring-damper system with a wheel. The wheel is assumed to be continuously in contact with the plate after impact. The governing partial differential equations of motion for displacements are converted into the ordinary differential equations in the time domain by using Galerkin’s method. Then, these sets of equations are solved by using the Runge-Kutta method. Several parameters such as vertical and horizontal velocities of the aircraft, volume fractions of the steel rebar in the reinforced concrete layer, and the different touchdown locations of the aircraft tire on the runway are considered in the numerical simulation. The results are compared with those of the ABAQUS, which is a commercial finite element code.

Keywords: elastic foundation, impact, moving load, thick plate

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Authors: Amitesh Goswami, Vishal Gulati, Annu Yadav

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In this paper, WEDM has been used to investigate the machining characteristics of Inconel-625 alloy. The machining characteristics namely material removal rate (MRR) and surface roughness (SR) have been investigated along with surface microstructure analysis using SEM and EDS of the machined surface. Taguchi’s L27 Orthogonal array design has been used by considering six varying input parameters viz. Pulse-on time (Ton), Pulse-off time (Toff), Spark Gap Set Voltage (SV), Peak Current (IP), Wire Feed (WF) and Wire Tension (WT) for the responses of interest. It has been found out that Pulse-on time (Ton) and Spark Gap Set Voltage (SV) are the most significant parameters affecting material removal rate (MRR) and surface roughness (SR) are. Microstructure analysis of workpiece was also done using Scanning Electron Microscope (SEM). It was observed that, variations in pulse-on time and pulse-off time causes varying discharge energy and as a result of which deep craters / micro cracks and large/ small number of debris were formed. These results were helpful in studying the effects of pulse-on time and pulse-off time on MRR and SR. Energy Dispersive Spectrometry (EDS) was also done to check the compositional analysis of the material and it was observed that Copper and Zinc which were initially not present in the Inconel 625, later migrated on the material surface from the brass wire electrode during machining

Keywords: MRR, SEM, SR, taguchi, Wire Electric Discharge Machining

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Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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Authors: Hesamaddin Khoshnoodi, Ahmad Rahbar Ranji

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Corrosion in steel structures is one of the most important issues that should be considered in designing and constructing. Corrosion reduces the cross section and load capacity of element and leads to costly damage of structures. In this paper, the corrosion has been modeled for moment stresses. Moreover, the steel beam has been modeled using ABAQUS advanced finite element software. The conclusions of this study demonstrated that the displacement of the analyzed composite steel girder bridge might increase.

Keywords: Abaqus, Corrosion, deformation, Steel Beam

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Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

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Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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Authors: Mehmet Ekici

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In this study, the fading time affecting the mechanical properties and microstructures of vermicular cast iron were studied. Pig iron and steel scrap weighing about 12 kg were charged into the high-frequency induction furnace crucible and completely melted for production of vermicular cast iron. The slag was skimmed using a common flux. After fading time was set at 1. 3 and 5 minutes. In this way, three vermicular cast iron was produced that same composition but different phase structures. The microstructure of specimens was investigated, and uni-axial tensile test and the Charpy impact test were performed, and their micro-hardness measurements were done in order to characterize the mechanical behaviours of vermicular cast iron.

Keywords: vermicular cast iron, fading time, hardness, tensile test and impact test

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Authors: Ben G. Weber, Michael Mateas

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We present a case-based reasoning technique for selecting build orders in a real-time strategy game. The case retrieval process generalizes features of the game state and selects cases using domain-specific recall methods, which perform exact matching on a subset of the case features. We demonstrate the performance of the technique by implementing it as a component of the integrated agent framework of McCoy and Mateas. Our results demonstrate that the technique outperforms nearest-neighbor retrieval when imperfect information is enforced in a real-time strategy game.

Keywords: case based reasoning, real time strategy systems, requirements elicitation, requirement analyst, artificial intelligence

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

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Authors: M. Duran Toksari, Berrin Ucarkus

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In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150-jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: delivery Times, learning effect, makespan, scheduling, total completion time

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Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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Authors: Dewi Tristantini, Jason Jonathan

Abstract:

Coronary Artery Disease (CAD) is one of the deathliest diseases which is caused by atherosclerosis. Atherosclerosis is a disease that plaque builds up inside the arteries. Plaque is made up of fat, cholesterol, calcium, platelet, and other substances found in blood. The current treatment of atherosclerosis is to provide antiplatelet therapy treatment, but such treatments often cause gastrointestinal irritation, muscle pain and hormonal imbalance. Mimusops elengi L.’s leaves can be utilized as a natural and cheap antiplatelet’s source because it contains flavonoids such as quertecin. Antiplatelet aggregation effect of Mimusops elengi L.’s leaves’ wet extract was measured by bleeding time on DDY strain mice with the test substances were given orally during the period of 8 days. The bleeding time was measured on first day and 9th day. Empirically, the dose which is used for humans is 8.5 g of leaves in 600 ml of water. This dose is equivalent to 2.1 g of leaves in 350 ml of water for mice. The extract was divided into 3 doses for mice: 0.05 ml/day; 0.1 ml/day; 0.2 ml/day. After getting the percentage of the increase in bleeding time, data were analyzed by analysis of variance test (Anova), followed by individual comparison within the groups by LSD test. The test substances above respectively increased bleeding time 21%, 62%, and 128%. As the conclusion, the 0.02 ml/day dose of Mimusops elengi L.’s leaves’ wet extract could increase bleeding time better than clopidogrel as positive controls with 110% increase in bleeding time.

Keywords: antiplatelets, atheroschlerosis, bleeding time, Mimusops elengi

Procedia PDF Downloads 264

Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

Abstract:

According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

Procedia PDF Downloads 453

Authors: Mounir Zili

Abstract:

We will introduce a new extension of the Brownian motion, that could serve to get a good model of many natural phenomena. It is a linear combination of a finite number of sub-fractional Brownian motions; that is why we will call it the mixed sub-fractional Brownian motion. We will present some basic properties of this process. Among others, we will check that our process is non-markovian and that it has non-stationary increments. We will also give the conditions under which it is a semi-martingale. Finally, the main features of its sample paths will be specified.

Keywords: fractal dimensions, mixed gaussian processes, sample paths, sub-fractional brownian motion

Procedia PDF Downloads 420

Authors: Alina Fedossova, Jose Jorge Sierra Molina

Abstract:

SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

Procedia PDF Downloads 309

Authors: Panupat Chaiworn, Soraya lama

Abstract:

We study the motion of particles in cylinders which are subjected to a sinusoidal vertical vibration. We measure the rising time of a large intruder from the bottom of the container to free surface of the bed particles and find that the rising time as a function of intruder density increases to a maximum and then decreases monotonically. The result is qualitatively accord to the previous findings in experiments using relative humidity of the bed particles and found speed convection of the bed particles containers it moving slowly, and the rising time of the intruder where a minimal instead of maximal rising time in the small density region was found. Our experimental results suggest that the topology of the container plays an important role in the Brazil nut effect.

Keywords: granular particles, Brazil nut effect, cylinder container, vertical vibration, convection

Procedia PDF Downloads 528