Search results for: multiuser- multi input single output

Authors: Timir Baran Roy, Luis Guerreiro, Ashutosh Bagchi

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Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as bridges, dams, high-rise buildings etc. There had been a substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as natural frequency, modal damping, and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototypes of such walls have been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated, and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Keywords: frequency domain decomposition (fdd), modal parameters, signal processing, stochastic subspace identification (ssi), time domain decomposition

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Authors: Nadine Maier, Martin Mensinger, Enea Tallushi

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In general, today, two types of launching bearings are used in the construction of large steel and steel concrete composite bridges. These are sliding rockers and systems with hydraulic bearings. The advantages and disadvantages of the respective systems are under discussion. During incremental launching, the center of the webs of the superstructure is not perfectly in line with the center of the launching bearings due to unavoidable tolerances, which may have an influence on the buckling behavior of the web plates. These imperfections are not considered in the current design against plate buckling, according to DIN EN 1993-1-5. It is therefore investigated whether the design rules have to take into account any eccentricities which occur during incremental launching and also if this depends on the respective launching bearing. Therefore, at the Technical University Munich, large-scale buckling tests were carried out on longitudinally stiffened plates under biaxial stresses with the two different types of launching bearings and eccentric load introduction. Based on the experimental results, a numerical model was validated. Currently, we are evaluating different parameters for both types of launching bearings, such as load introduction length, load eccentricity, the distance between longitudinal stiffeners, the position of the rotation point of the spherical bearing, which are used within the hydraulic bearings, web, and flange thickness and imperfections. The imperfection depends on the geometry of the buckling field and whether local or global buckling occurs. This and also the size of the meshing is taken into account in the numerical calculations of the parametric study. As a geometric imperfection, the scaled first buckling mode is applied. A bilinear material curve is used so that a GMNIA analysis is performed to determine the load capacity. Stresses and displacements are evaluated in different directions, and specific stress ratios are determined at the critical points of the plate at the time of the converging load step. To evaluate the load introduction of the transverse load, the transverse stress concentration is plotted on a defined longitudinal section on the web. In the same way, the rotation of the flange is evaluated in order to show the influence of the different degrees of freedom of the launching bearings under eccentric load introduction and to be able to make an assessment for the case, which is relevant in practice. The input and the output are automatized and depend on the given parameters. Thus we are able to adapt our model to different geometric dimensions and load conditions. The programming is done with the help of APDL and a Python code. This allows us to evaluate and compare more parameters faster. Input and output errors are also avoided. It is, therefore, possible to evaluate a large spectrum of parameters in a short time, which allows a practical evaluation of different parameters for buckling behavior. This paper presents the results of the tests as well as the validation and parameterization of the numerical model and shows the first influences on the buckling behavior under eccentric and multi-axial load introduction.

Keywords: buckling behavior, eccentric load introduction, incremental launching, large scale buckling tests, multi axial stress states, parametric numerical modelling

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Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

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Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

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Authors: Shilpa Kulkarni, Sujata Patrikar

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A single-mode fiber directional coupler is modeled and simulated for its application in medical field. Various fiber devices based on evanescent field absorption, interferometry, couplers, resonators, tip coated fibers, etc, have been developed so far, suitable for medical application. This work focuses on the possibility of sensing by single mode fiber directional coupler. In the preset work, a fiber directional coupler is modeled to detect the changes taking place in the surrounding medium optoelectronically. In this work, waveguiding characteristics of the fiber are studied in depth. The sensor is modeled and simulated by finding photocurrent, sensitivity and detection limit by varying various parameters of the directional coupler. The device is optimized for the best possible output. It is found that the directional coupler shows measurable photocurrents and good sensitivity with coupling length in micrometers. It is thus a miniature device, hence, suitable for medical applications.

Keywords: single mode fiber directional coupler, modeling and simulation of fiber directional coupler sensor, biomolecular sensing, medical sensor device

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Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

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When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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Authors: Morteza Sharifhasan, Davoud Hosseini, Mohammad. R. Salimpour

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The geothermal energy is considered as a worldwide important renewable energy in recent years due to rising environmental pollution concerns. Low- and medium-grade geothermal heat (< 200 ºC) is commonly employed for space heating and in domestic hot water supply. However, there is also much interest in converting the abundant low- and medium-grade geothermal heat into electrical power. The Iranian Ministry of Power - through the Iran Renewable Energy Organization (SUNA) – is going to build the first Geothermal Power Plant (GPP) in Iran in the Sabalan area in the Northwest of Iran. This project is a 5.5 MWe single flash steam condensing power plant. The efficiency of GPPs is low due to the relatively low pressure and temperature of the saturated steam. In addition to GPPs, Gas Turbines (GTs) are also known by their relatively low efficiency. The Iran ministry of Power is trying to increase the efficiency of these GTs by adding bottoming steam cycles to the GT to form what is known as combined gas/steam cycle. One of the most effective methods for increasing the efficiency is combined heat and power (CHP). This paper investigates the feasibility of superheating the saturated steam that enters the steam turbine of the Sabalan GPP (SGPP-1) to improve the energy efficiency and power output of the GPP. This purpose is achieved by combining the GPP with two 3.5 MWe GTs. In this method, the hot gases leaving GTs are utilized through a superheater similar to that used in the heat recovery steam generator of combined gas/steam cycle. Moreover, brine separated in the separator, hot gases leaving GTs and superheater are used for the supply of domestic hot water (in this paper, the cycle combined of GTs and CHP systems is named the modified SGPP-1) . In this research, based on the Heat Balance presented in the basic design documents of the SGPP-1, mathematical/numerical model of the power plant are developed together with the mentioned GTs and CHP systems. Based on the required hot water, the amount of hot gasses needed to pass through CHP section directly can be adjusted. For example, during summer when hot water is less required, the hot gases leaving both GTs pass through the superheater and CHP systems respectively. On the contrary, in order to supply the required hot water during the winter, the hot gases of one of the GTs enter the CHP section directly, without passing through the super heater section. The results show that there is an increase in thermal efficiency up to 40% through using the modified SGPP-1. Since the gross efficiency of SGPP-1 is 9.6%, the achieved increase in thermal efficiency is significant. The power output of SGPP-1 is increased up to 40% in summer (from 5.5MW to 7.7 MW) while the GTs power output remains almost unchanged. Meanwhile, the combined-cycle power output increases from the power output of the two separate plants of 12.5 MW [5.5+ (2×3.5)] to the combined-cycle power output of 14.7 [7.7+(2×3.5)]. This output is more than 17% above the output of the two separate plants. The modified SGPP-1 is capable of producing 215 T/Hr hot water ( 90 ºC ) for domestic use in the winter months.

Keywords: combined cycle, chp, efficiency, gas turbine, geothermal power plant, gas turbine, power output

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Authors: Ji Hyung Park, Dong-Hyun Seo, Young-Jin Jung, Han Sung Kim

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The aim of this study is to evaluate the effects of the laser and partial vibration stimulation on the mice tibia with morphological characteristics. Twenty female C57BL/6 mice (12 weeks old) were used for the experiment. The study was carried out on four groups of animals each consisting of five mice. Four groups of mice were ovariectomized. Animals were scanned at 0 and 2 weeks after ovariectomy by using micro-computed tomography to estimate morphological characteristics of tibial trabecular bone. Morphological analysis showed that structural parameters of multi-stimuli group appear significantly better phase in BV/TV, BS/BV, Tb.Th, Tb.N, Tb.Sp, and Tb.pf than single stimulation groups. However, single stimulation groups didn’t show significant effect on tibia with Sham group. This study suggests that multi-stimuli may restrain the change as the degenerate phase on osteoporosis in the mice tibia.

Keywords: laser, partial vibration, osteoporosis, in-vivo micro-CT, mice

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Authors: E. Ramprasath, P. Manojkumar, P. Veena

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Proposed paper dealt with the modelling and analysis of induction motor based on the mathematical expression using the graphical programming environment of Laboratory Virtual Instrument Engineering Workbench (LabVIEW). Induction motor modelling with the mathematical expression enables the motor to be simulated with the various required parameters. Owing to the invention of variable speed drives study about the induction motor characteristics became complex.In this simulation motor internal parameter such as stator resistance and reactance, rotor resistance and reactance, phase voltage, frequency and losses will be given as input. By varying the speed of motor corresponding parameters can be obtained they are input power, output power, efficiency, torque induced, slip and current.

Keywords: induction motor, LabVIEW software, modelling and analysi, electrical and mechanical characteristics of motor

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Authors: Vipresh Mehta , Aman Abhishek, Jatin Batra, Gautam Iyer

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Huge amount of solar radiation reaching the earth can be harnessed to provide electricity through Photo voltaic (PV) panels. The solar PV is an exciting technology but suffers from low efficiency. A study on low efficiency in multi MW solar power plants reveals that the electric yield of the PV modules is reduced due to reflection of the irradiation from the sun and when a module’s temperature is elevated, as there is decrease in the voltage and efficiency. We intend to alter the structure of the PV system, We also intend to improve the efficiency of the Solar Photo Voltaic Panels by active cooling to reduce the temperature losses considerably and decrease reflection losses to some extent. Reflectors/concentrators and anti-reflecting coatings are also used to intensify the amount of output produced from the system. Apart from this, transformer-less Grid-tied Inverter. And also, a T-LCL immitance circuit is used to reduce the harmonics and produce a constant output from the entire system.

Keywords: PV panels, efficiency improvement, active cooling, quantum dots, organic-inorganic hybrid 3D panel, ground water tunneling

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani

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In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.

Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer

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Authors: Dongjoo Kim

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Effective control of sloshing in a liquid container is an important issue to be resolved in many applications. In this study, numerical simulations are performed to design the velocity profile of rectangular container and investigate the effectiveness of input shaping for sloshing control. Trapezoidal profiles of container velocity are chosen to be reference commands and they are convolved with a series of impulses to generate shaped ones that induce minimal residual oscillations. The performances of several input shapers are compared from the viewpoint of transient peak and residual oscillations of sloshing. Results show that sloshing can be effectively controlled by input shaping (Supported by the NRF programs, NRF-2015R1D1A1A01059675, of Korean government).

Keywords: input shaping, rectangular container, sloshing, trapezoidal profile

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Authors: Mohamed S. El-Asfoury, Ahmed Abdel-Moneim, Mohamed N. A. Nasr

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The current study uses finite element modeling to investigate and analyze a modified form of the from the conventional equal channel multi-angular pressing (ECMAP), using non-equal channels, on the workpiece material plastic deformation. The modified process non-equal channel multi-angular extrusion (NECMAE) is modeled using two-dimensional plane strain finite element model built using the commercial software ABAQUS. The workpiece material used is pure aluminum. The model was first validated by comparing its results to analytical solutions for single-pass equal channel angular extrusion (ECAP), as well as previously published data. After that, the model was used to examine the effects of different % of reductions of the area (for the second stage) on material plastic deformation, corner gap, and required the load. Three levels of reduction in the area were modeled; 10%, 30%, and 50%, and compared to single-pass and double-pass ECAP. Cases with a higher reduction in the area were found to have smaller corner gaps, higher and much uniform plastic deformation, as well as higher required loads. The current results are mainly attributed to the back pressure effects exerted by the second stage, as well as strain hardening effects experienced during the first stage.

Keywords: non-equal channel angular extrusion, multi-pass, sever plastic deformation, back pressure, Finite Element Modelling (FEM)

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Authors: Anthony John Walker, Glen Bright

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The challenge faced by manufactures, when producing custom products, is that each product needs exact components. This can cause work-in-process instability due to component matching constraints imposed on assembly cells. Clearing type flow control policies have been used extensively in mediating server access between multiple arrival processes. Although the stability and performance of clearing policies has been well formulated and studied in the literature, the growth in arrival to departure sequence disorder for each arriving job, across a serving resource, is still an area for further analysis. In this paper, a closed form industrial model has been formulated that characterizes arrival-to-departure sequence disorder through stable manufacturing systems under clearing type flow control policy. Specifically addressed are the effects of sequence disorder imposed on a downstream assembly cell in terms of work-in-process instability induced through component matching constraints. Results from a simulated manufacturing system show that steady state average sequence disorder in parallel upstream processing cells can be balanced in order to decrease downstream assembly system instability. Simulation results also show that the closed form model accurately describes the growth and limiting behavior of average sequence disorder between parts arriving and departing from a manufacturing system flow controlled via clearing policy.

Keywords: assembly system constraint, custom products, discrete sequence disorder, flow control

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: genetic algorithm, rsm, biodiesel, karanja

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Authors: Hassan H. Abuelhassan, M. Ali Badawi, Abdelrahman A. Elbadawi, Adam A. Elbashir

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In this paper, the effect of the injected current and temperature into the output power of the laser diode module operating at 808nm were applied, studied and discussed. Low power diode laser was employed as a source. The experimental results were demonstrated and then the output power of laser diode module operating at 808nm was clearly changed by the thermal temperature and injected current. The output power increases by the increasing the injected current and temperature. We also showed that the increasing of the injected current results rising in heat, which also, results into decreasing of the laser diode output power during the highest temperature as well. The best ranges of characteristics made by diode module operating at 808nm were carefully handled and determined.

Keywords: laser diode, light amplification, injected current, output power

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Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

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Authors: A. A. Hassani, M. Nasri Nasrabadi

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According to population growth and increasing water needs of industrial and agricultural sections and lack of existing water sources, also increases of wastewater and new wastewater treatment plant construction’s high costs, it is inevitable to reuse wastewater with the approach of increasing wastewater treatment capacity and output sewage quality. In this regard, the first sewage reuse plan in industrial uses was designed with the approach of qualitative and quantitative improvement due to the increased organic load of the output sewage of Qom Shokohieh city’s’ in wastewater treatment plant. This research investigated qualitative factors COD, BOD, TSS, TDS, and input and output heavy metal of MBR-RO system and ability of increase wastewater acceptance capacity by existing in wastewater treatment plant. For this purpose, experimental results of seven-month navigation system have been used from 07/01/2013 to 02/01/2014. Existing data analysis showed that MBR system is able to remove 93.2% COD, 94.4% BOD, 13.8% TDS, 98% heavy metals and RO system is able to remove 98.9% TDS. This study showed that MBR-RO integration system is able to increase the capacity of refinery by 30%.

Keywords: industrial wastewater, wastewater reuse, MBR, RO

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Authors: Hasan A Al-Asadi, Ali Samir, Afrah Turki Awad, Ali Basem

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Integrating the phase change material (PCM) with photovoltaic (PV) panels is one of the effective techniques to minimize the PV panel temperature and increase their electric output. In order to investigate the impact of the PCM on the electric output of the PV panels for a whole year, a lumped-distributed parameter model for the PV-PCM module has been developed. This development has considered the impact of the PCM density variation between the solid phase and liquid phase. This contribution will increase the assessment accuracy of the electric output of the PV-PCM module. The second contribution is to assess the impact of the expanded composite graphite-PCM on the PV electric output in Milan for a whole year. The novel one-dimensional model has been solved using MATLAB software. The results of this model have been validated against literature experiment work. The weather and the solar radiation data have been collected. The impact of expanded graphite-PCM on the electric output of the PV panel for a whole year has been investigated. The results indicate this impact has an enhancement rate of 2.39% for the electric output of the PV panel in Milan for a whole year.

Keywords: PV panel efficiency, PCM, numerical model, solar energy

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Touil Djamal, Fergani Zineb

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In this study, an Organic Rankine Cycle (ORC) with Cyclohexane working fluid is proposed for cogeneration in the cement industry. In this regard: first, a parametric study is conducted to evaluate the effects of some key parameters on the system performances. Next, single and multi-objective optimizations are performed to achieve the system optimal design. The optimization considers the exergy efficiency, the cost per exergy unit and the environmental impact of the net produced power as objective functions. Finally, exergy, exergoeconomic and exergoenvironmental analysis of the cycle is carried out at the optimum operating conditions. The results show that the turbine inlet pressure, the pinch point temperature difference and the heat transfer fluid temperature have significant effects on the performances of the ORC system.

Keywords: organic rankine cycle, multi-objective optimization, exergy, exergoeconomic, exergoenvironmental, multi-objective optimisation, organic rankine cycle, cement plant

Procedia PDF Downloads 248

Authors: Mahmoud S. El-Sebaey, Asko Ellman, Ahmed Hegazy, Tarek Ghonim

Abstract:

Due to population growth, the need for drinkable healthy water is highly increased. Consequently, and since the conventional sources of water are limited, researchers devoted their efforts to oceans and seas for obtaining fresh drinkable water by thermal distillation. The current work is dedicated to the design and fabrication of modified solar still model, as well as conventional solar still for the sake of comparison. The modified still is single slope double basin solar still. The still consists of a lower basin with a dimension of 1000 mm x 1000 mm which contains the sea water, as well as the top basin that made with 4 mm acrylic, was temporarily kept on the supporting strips permanently fixed with the side walls. Equally ten spaced vertical glass strips of 50 mm height and 3 mm thickness were provided at the upper basin for the stagnancy of the water. Window glass of 3 mm was used as the transparent cover with 23° inclination at the top of the still. Furthermore, the performance evaluation and comparison of these two models in converting salty seawater into drinkable freshwater are introduced, analyzed and discussed. The experiments were performed during the period from June to July 2018 at seawater depths of 2, 3, 4 and 5 cm. Additionally, the solar still models were operated simultaneously in the same climatic conditions to analyze the influence of the modifications on the freshwater output. It can be concluded that the modified design of double basin single slope solar still shows the maximum freshwater output at all water depths tested. The results showed that the daily productivity for modified and conventional solar still was 2.9 and 1.8 dm³/m² day, indicating an increase of 60% in fresh water production.

Keywords: freshwater output, solar still, solar energy, thermal desalination

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

Abstract:

Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

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Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

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Authors: Linyu Wang, Mingjun Zhu, Jianhong Xiang, Hanyu Jiang

Abstract:

Aiming at the problem that the spectral efficiency of hybrid precoding (HP) is too low in the current millimeter wave (mmWave) massive multiple input multiple output (MIMO) system, this paper proposes a digital joint equivalent channel hybrid precoding algorithm, which is based on the introduction of digital encoding matrix iteration. First, the objective function is expanded to obtain the relation equation, and the pseudo-inverse iterative function of the analog encoder is derived by using the pseudo-inverse method, which solves the problem of greatly increasing the amount of computation caused by the lack of rank of the digital encoding matrix and reduces the overall complexity of hybrid precoding. Secondly, the analog coding matrix and the millimeter-wave sparse channel matrix are combined into an equivalent channel, and then the equivalent channel is subjected to Singular Value Decomposition (SVD) to obtain a digital coding matrix, and then the derived pseudo-inverse iterative function is used to iteratively regenerate the simulated encoding matrix. The simulation results show that the proposed algorithm improves the system spectral efficiency by 10~20%compared with other algorithms and the stability is also improved.

Keywords: mmWave, massive MIMO, hybrid precoding, singular value decompositing, equivalent channel

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Authors: Tejinder Singh

Abstract:

This paper describes a new more efficient Hydraulic System which uses lesser work to produce more output. Conventional Hydraulic System like Hydraulic Lifts and Rams use lots of water to be pumped to produce output. TejHydroLift will do the equal amount of force with lesser input of water. The paper will show that force applied can be increased manifold without requiring to move smaller force by more distance which used to be required in Conventional Hydraulic Lifts. The paper describes one of the configurations of TejHydroLift System called “Slim Antenna TejHydroLift Configuration”. The TejHydroLift uses lesser water and hence demands lesser work to be performed to move the same load.

Keywords: alternate, hydraulic system, efficient, TejHydroLift

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Authors: Rajeev Kumar Bedi, Jaswinder Singh, Sunil Kumar Gupta

Abstract:

Cloud storage is a model of online data storage where data is stored in virtualized pool of servers hosted by third parties (CSPs) and located in different geographical locations. Cloud storage revolutionized the way how users access their data online anywhere, anytime and using any device as a tablet, mobile, laptop, etc. A lot of issues as vendor lock-in, frequent service outage, data loss and performance related issues exist in single cloud storage systems. So to evade these issues, the concept of multi cloud storage introduced. There are a lot of multi cloud storage systems exists in the market for mobile devices. In this article, we are providing comparison of four multi cloud storage systems for mobile devices Otixo, Unclouded, Cloud Fuze, and Clouds and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on three mobile phones Nexus 5, Moto G and Nexus 7 tablet and using Wi-Fi network. Finally, open research challenges and future scope are discussed.

Keywords: cloud storage, multi cloud storage, vendor lock-in, mobile devices, mobile cloud computing

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Authors: K. M. Alsager, N. O. Alshehri

Abstract:

In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example.

Keywords: single valued neutrosophic fuzzy set, single valued neutrosophic fuzzy hesitant set, rough set, single valued neutrosophic hesitant fuzzy rough set

Procedia PDF Downloads 244