Search results for: realistic simulation

Authors: Hashem M. Alargha, Mohammad O. Hamdan, Waseem H. Aziz

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Aerobatic and military pilots are subjected to high gravitational forces that could cause blackout, physical injuries or death. A CFD simulation using fluid-solid interactions scheme has been conducted to investigate the gravitational effects and hazards inside cerebral aneurysms. Medical data have been used to derive the size and geometry of a simple aneurysm on a T-shaped bifurcation. The results show that gravitational force has no effect on maximum Wall Shear Stress (WSS); hence, it will not cause aneurysm initiation/formation. However, gravitational force cause causes hypertension which could contribute to aneurysm rupture.

Keywords: aneurysm, cfd, wall shear stress, gravity, fluid dynamics, bifurcation artery

Procedia PDF Downloads 368

Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

Procedia PDF Downloads 418

Authors: Kyo Jin An, Bukyo Seo, Young-Chul Park

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The current trend in car market is increase of parts of automobile and weight in vehicle. It comes from improvement of vehicle performance. Outer tie rod is a part of component of steering system and it is lighter than the others. But, weight lightening is still required for improvement of car mileage. So, we have presented a model of aluminized outer tie rod, but the process of fabrication has to be checked to manufacture the product. Therefore, we have anticipated forming load, die stress and abrasion to use the program of forging interpretation in the part of hot forging process of outer tie rod in this study. Also, we have implemented the experiments design to use the table of orthogonal arrays to reduce the forming load.

Keywords: forming load, hot forging, orthogonal array, outer tie rod (OTR), multi–step forging

Procedia PDF Downloads 433

Authors: Akinwumi Omotayo, Badu-B Apraku, Joseph Olobasola, Petra Abdul Saghir, Yinka Sobowale

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In southwestern Nigeria, climate change has led to loss of at least two months of rainfall. Consequently, only one cycle of maize can now be grown because of the shorter duration of rainy season as against two cycles in the past. The Early and Extra-early maturing varieties of maize were originally developed for the semi-arid and arid zones of West and Central Africa where there are seasonal challenges of water threatening optimum performance of the traditional maize grown, which are commonly late in maturity (115 to 120 days). The early varieties of maize mature in 90 to 95 days; while the Extra-Early maize varieties reach physiological maturity in less than 90 days. It was broadly hypothesized that the extra early varieties of maize could mitigate the effects of climate change in southwestern Nigeria with higher levels of rainfall by reinstating the original two cycles of rain-fed maize crop. Trials were therefore carried out in southwestern Nigeria on the possibility of adapting the extra early maize to mitigate the effects of climate change. The trial was the Mother/Baby design. The mother trial involves the evaluation of extra-early varieties following ideal recommendations and closely supervised centrally at the University research farm and the Agricultural Development Programmes (ADPs). This requires farmers to observe and evaluate the technology and the management regime meant to precede the second stage of evaluation at several satellite farmers field managed by selected farmers. The Baby Trial is expected to provide a realistic assessment of the technology by farmers in their own environment. A stratified selection of thirty farmers for the Baby Trial ensured appropriate representation across the different categories of the farming population by age and gender. Data from the trials indicate that extra early maize can be grown in two cycles rain fed in south west Nigeria and a third and fourth cycle could be obtained with irrigation. However the long duration varieties outyielded the extra early maize in both the mother and baby trials. When harvested green, the extra early maize served as source of food between March and May when there was scarcity of food. This represents a major advantage. The study recommends that further work needs to be done to improve the yield of extra early maize to encourage farmers to adopt.

Keywords: adaptation, climate change, extra early, maize varieties, mitigation

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Authors: Sanam Haseen, Abdul Bari

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In this paper a three stage multivariate programming problem with random survey cost and variances as random variables has been formulated as a non-linear stochastic programming problem. The problem has been converted into an equivalent deterministic form using chance constraint programming and modified E-modeling. An empirical study of the problem has been done at the end of the paper using R-simulation.

Keywords: chance constraint programming, modified E-model, stochastic programming, stratified sample surveys, three stage sample surveys

Procedia PDF Downloads 458

Authors: Karina C. Azzolin, Luis E. Kosteski, Alisson S. Milani, Raquel C. Zydeck

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This work aims to represent Numerically tests experimentally developed in reduced scale walls with horizontal and inclined cuts by using the Lattice Discrete Element Method (LDEM) implemented On de Abaqus/explicit environment. The cuts were performed with depths of 20%, 30%, and 50% On the walls subjected to centered and eccentric loading. The parameters used to evaluate the numerical model are its strength, the failure mode, and the in-plane and out-of-plane displacements.

Keywords: structural masonry, wall chases, small scale, numerical model, lattice discrete element method

Procedia PDF Downloads 178

Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: Muqaddas Javed, Muhammad Hanif

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The generalized multivariate ratio and regression type estimators for population mean are suggested under multi-phase stratified systematic sampling (MPSSS) using multi auxiliary information. Estimators are developed under the two different situations of availability of auxiliary information. The expressions of bias and mean square error (MSE) are developed. Special cases of suggested estimators are also discussed and simulation study is conducted to observe the performance of estimators.

Keywords: generalized estimators, multi-phase sampling, stratified random sampling, systematic sampling

Procedia PDF Downloads 729

Authors: Rawaa Maher, Ahmed Allam, Haruichi Kanaya, Adel B. Abdelrahman

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In this paper, a compact, high-efficiency integrated rectenna is presented to operate in the 2.45 GHz band. A comparison between two rectifier topologies is performed to verify the benefits of removing the matching network from the rectifier. A rectifier high conversion efficiency of 74.1% is achieved. To complete the rectenna system, a novel omnidirectional antenna with high gain (3.72 dB) and compact size (25 mm * 29 mm) is designed and fabricated. The same antenna is used with a reflector for raising the gain to nearly 8.3 dB. The simulation and measurement results of the antenna are in good agreement.

Keywords: internet of things, integrated rectenna, rectenna, RF energy harvesting, wireless sensor networks(WSN)

Procedia PDF Downloads 182

Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

Procedia PDF Downloads 492

Authors: Y. Landkocz, P. Gosset, A. Héliot, C. Corbière, C. Vendeville, V. Keravec, S. Billet, A. Verdin, C. Monteil, D. Préterre, J-P. Morin, F. Sichel, T. Douki, P. J. Martin

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Air Pollution produced by automobile traffic is one of the main sources of pollutants in urban atmosphere and is largely due to exhausts of the diesel engine powered vehicles. The International Agency for Research on Cancer, which is part of the World Health Organization, classified in 2012 diesel engine exhaust as carcinogenic to humans (Group 1), based on sufficient evidence that exposure is associated with an increased risk for lung cancer. Amongst the strategies aimed at limiting exhausts in order to take into consideration the health impact of automobile pollution, filtration of the emissions and use of biofuels are developed, but their toxicological impact is largely unknown. Diesel exhausts are indeed complex mixtures of toxic substances difficult to study from a toxicological point of view, due to both the necessary characterization of the pollutants, sampling difficulties, potential synergy between the compounds and the wide variety of biological effects. Here, we studied the potential indirect genotoxicity of emission of Diesel engines through on-line exposure of rats in inhalation chambers to a subchronic high but realistic dose. Following exposure to standard gasoil +/- rapeseed methyl ester either upstream or downstream of a particle filter or control treatment, rats have been sacrificed and their lungs collected. The following indirect genotoxic parameters have been measured: (i) telomerase activity and telomeres length associated with rTERT and rTERC gene expression by RT-qPCR on frozen lungs, (ii) γH2AX quantification, representing double-strand DNA breaks, by immunohistochemistry on formalin fixed-paraffin embedded (FFPE) lung samples. These preliminary results will be then associated with global cellular response analyzed by pan-genomic microarrays, monitoring of oxidative stress and the quantification of primary DNA lesions in order to identify biological markers associated with a potential pro-carcinogenic response of diesel or biodiesel, with or without filters, in a relevant system of in vivo exposition.

Keywords: diesel exhaust exposed rats, γH2AX, indirect genotoxicity, lung carcinogenicity, telomerase activity, telomeres length

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

Procedia PDF Downloads 195

Authors: Suraj Sam Issaka, Anita Asamoah, Abass Gibrilla, Joseph Richmond Fianko

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Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that can form in edible oils during repeated frying and accumulate in fried foods. This study assesses the chances of health risks (carcinogenic and non-carcinogenic) due to PAHs levels in popular finger foods (bean cakes, plantain chips, doughnuts) fried in edible oils (mixed vegetable, sunflower, soybean) from the Ghanaian market. Employing probabilistic health risk assessment that considers variability and uncertainty in exposure and risk estimates provides a more realistic representation of potential health risks. Monte Carlo simulations with 10,000 iterations were used to estimate carcinogenic, mutagenic, and non-carcinogenic risks for different age groups (A: 6-10 years, B: 11-20 years, C: 20-70 years), food types (bean cake, plantain chips, doughnut), oil types (soybean, mixed vegetable, sunflower), and re-usage frying oil frequencies (once, twice, thrice). Our results suggest that, for age Group A, doughnuts posed the highest probability of carcinogenic risk (91.55%) exceeding the acceptable threshold, followed by bean cakes (43.87%) and plantain chips (7.72%), as well as the highest probability of unacceptable mutagenic risk (89.2%), followed by bean cakes (40.32%). Among age Group B, doughnuts again had the highest probability of exceeding carcinogenic risk limits (51.16%) and mutagenic risk limits (44.27%). At the same time, plantain chips exhibited the highest maximum carcinogenic risk. For adults age Group C, bean cakes had the highest probability of unacceptable carcinogenic (50.88%) and mutagenic risks (46.44%), though plantain chips showed the highest maximum values for both carcinogenic and mutagenic risks in this age group. Also, on non-carcinogenic risks across different age groups, it was found that age Group A) who consumed doughnuts had a 68.16% probability of a hazard quotient (HQ) greater than 1, suggesting potential cognitive impairment and lower IQ scores due to early PAH exposure. This group also faced risks from consuming plantain chips and bean cake. For age Group B, the consumption of plantain chips was associated with a 36.98% probability of HQ greater than 1, indicating a potential risk of reduced lung function. In age Group C, the consumption of plantain chips was linked to a 35.70% probability of HQ greater than 1, suggesting a potential risk of cardiovascular diseases.

Keywords: PAHs, fried foods, carcinogenic risk, non-carcinogenic risk, Monte Carlo simulations

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Authors: Burak Yildirim, Muhsin Tunay Gençoğlu

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A microgrid (MG) is a small power grid composed of localized medium or low level power generation, storage systems, and loads. In this paper, the effects of a MG on power systems voltage stability are shown. The MG model, designed to demonstrate the effects of the MG, was applied to the IEEE 14 bus power system which is widely used in power system stability studies. Eigenvalue and modal analysis methods were used in simulation studies. In the study results, it is seen that MGs affect system voltage stability positively by increasing system voltage instability limit value for buses of a power system in which MG are placed.

Keywords: eigenvalue analysis, microgrid, modal analysis, voltage stability

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Authors: Ishtiaq Wahid, Masood Ahmad, Nighat Ayub, Sajad Ali

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Lifetime of a wireless sensor network (WSN) is directly proportional to the energy consumption of its constituent nodes. Routing in wireless sensor network is very challenging due its inherit characteristics. In hierarchal routing the sensor filed is divided into clusters. The cluster-heads are selected from each cluster, which forms a hierarchy of nodes. The cluster-heads are used to transmit the data to the base station while other nodes perform the sensing task. In this way the lifetime of the network is increased. In this paper a comparative study of hierarchal routing protocols are conducted. The simulation is done in NS-2 for validation.

Keywords: WSN, cluster, routing, sensor networks

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Authors: L. Yettou

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In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models , level density, level density a-parameter., Empire code, Talys code.

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Authors: Amir Mahdavi

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In this paper a highly linear CMOS low noise amplifier (LNA) for ultra-wideband (UWB) applications is proposed. The proposed LNA uses a linearization technique to improve second and third-order intercept points (IIP3). The linearity is cured by repealing the common-mode section of all intermodulation components from the cascade topology current with optimization of biasing current use symmetrical and asymmetrical circuits for biasing. Simulation results show that maximum gain and noise figure are 6.9dB and 3.03-4.1dB over a 3.1–10.6 GHz, respectively. Power consumption of the LNA core and IIP3 are 2.64 mW and +4.9dBm respectively. The wideband input impedance matching of LNA is obtained by employing a degenerating inductor (|S11|<-9.1 dB). The circuit proposed UWB LNA is implemented using 0.18 μm based CMOS technology.

Keywords: highly linear LNA, low-power LNA, optimal bias techniques

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Authors: S. Malisuwan, J. Sivaraks, N. Madan, N. Suriyakrai

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The ever going evolution of advanced wireless technologies makes it financially impossible for military operations to completely manufacture their own equipment. Therefore, Commercial-Off-The-Shelf (COTS) and Modified-Off-The-Shelf (MOTS) are being considered in military mission with low-cost modifications. In this paper, we focus on the LTE multicast systems for military communication systems under tactical environments with jamming condition. We examine the influence of the colored noise jamming on the performance of the LTE multicast systems in terms of the average throughput. The simulation results demonstrate the degradation of the average throughput for different dynamic ranges of the colored noise jamming versus average SNR.

Keywords: performance, LTE, multicast, jamming, throughput

Procedia PDF Downloads 418

Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

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Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

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Authors: Shoji Katagiri, Hugang Han

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This paper clarifies the role of ICT capital in Economic Growth. Albeit ICT remarkably contributes to economic growth, there are few studies on ICT capital in ICT sector from theoretical point of view. In this paper, production function of ICT which is used as input of intermediate good in final good and ICT sectors is incorporated into our model. In this setting, we analyze the role of ICT on balance growth path and show the possibility of general equilibrium solutions for this model. Through the simulation of the equilibrium solutions, we find that when ICT impacts on economy and economic growth increases, it is necessary that increases of efficiency at ICT sector and of accumulation of non-ICT and ICT capitals occur simultaneously.

Keywords: endogenous economic growth, ICT, intensity, capital accumulation

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Authors: F. Rarbi, D. Dzahini, W. Uhring

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In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm². The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: A. Cherifi, B. S. Bouazza, A. O. Dahman, B. Yagoubi

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Transmission over Optical channels will introduce inter-symbol interference (ISI) as well as inter-channel (or inter-carrier) interference (ICI). To decrease the effects of ICI, this paper proposes equalizer for the Optical OFDM system based on the fractional Fourier transform (FrFFT). In this FrFT-OFDM system, traditional Fourier transform is replaced by fractional Fourier transform to modulate and demodulate the data symbols. The equalizer proposed consists of sampling the received signal in the different time per time symbol. Theoretical analysis and numerical simulation are discussed.

Keywords: OFDM, fractional fourier transform, internet and information technology

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Authors: Arash Dalili, Hamed Tahmouressi, Mina Hoorfar

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Advances in lab-on-a-chip (LOC) devices have led to significant advances in the manipulation, separation, and isolation of particles and cells. Among the different active and passive particle manipulation methods, dielectrophoresis (DEP) has been proven to be a versatile mechanism as it is label-free, cost-effective, simple to operate, and has high manipulation efficiency. DEP has been applied for a wide range of biological and environmental applications. A popular form of DEP devices is the continuous manipulation of particles by using co-planar slanted electrodes, which utilizes a sheath flow to focus the particles into one side of the microchannel. When particles enter the DEP manipulation zone, the negative DEP (nDEP) force generated by the slanted electrodes deflects the particles laterally towards the opposite side of the microchannel. The lateral displacement of the particles is dependent on multiple parameters including the geometry of the electrodes, the width, length and height of the microchannel, the size of the particles and the throughput. In this study, COMSOL Multiphysics® modeling along with experimental studies are used to investigate the effect of the aforementioned parameters. The electric field between the electrodes and the induced DEP force on the particles are modelled by COMSOL Multiphysics®. The simulation model is used to show the effect of the DEP force on the particles, and how the geometry of the electrodes (width of the electrodes and the gap between them) plays a role in the manipulation of polystyrene microparticles. The simulation results show that increasing the electrode width to a certain limit, which depends on the height of the channel, increases the induced DEP force. Also, decreasing the gap between the electrodes leads to a stronger DEP force. Based on these results, criteria for the fabrication of the electrodes were found, and soft lithography was used to fabricate interdigitated slanted electrodes and microchannels. Experimental studies were run to find the effect of the flow rate, geometrical parameters of the microchannel such as length, width, and height as well as the electrodes’ angle on the displacement of 5 um, 10 um and 15 um polystyrene particles. An empirical equation is developed to predict the displacement of the particles under different conditions. It is shown that the displacement of the particles is more for longer and lower height channels, lower flow rates, and bigger particles. On the other hand, the effect of the angle of the electrodes on the displacement of the particles was negligible. Based on the results, we have developed an optimum design (in terms of efficiency and throughput) for three size separation of particles.

Keywords: COMSOL Multiphysics, Dielectrophoresis, Microfluidics, Particle separation

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Subhankar Karmakar, Madhan Kumar Vasudevan, Manivannan Muniyandi

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Thermal Grill Illusion (TGI) elicits a strong and often painful sensation of burn when interlacing warm and cold stimuli that are individually non-painful, excites thermoreceptors beneath the skin. Among several theories of TGI, the “disinhibition” theory is the most widely accepted in the literature. According to this theory, TGI is the result of the disinhibition or unmasking of the pain-sensitive HPC (Heat-Pinch-Cold) nerve fibers due to the inhibition of cold-sensitive nerve fibers that are responsible for masking HPC nerve fibers. Although researchers focused on understanding TGI throughexperiments and models, none of them investigated the prediction of TGI pain intensity through a computational model. Furthermore, the comparison of psychophysically perceived TGI intensity with neurophysiological models has not yet been studied. The prediction of pain intensity through a computational model of TGI can help inoptimizing thermal displays and understanding pathological conditions related to temperature perception. The current studyfocuses on developing a computational model to predict the intensity of TGI pain and experimentally observe the perceived TGI pain. The computational model is developed based on the disinhibition theory and by utilizing the existing popular models of warm and cold receptors in the skin. The model aims to predict the neuronal activity of the HPC nerve fibers. With a temperature-controlled thermal grill setup, fifteen participants (ten males and five females) were presented with five temperature differences between warm and cold grills (each repeated three times). All the participants rated the perceived TGI pain sensation on a scale of one to ten. For the range of temperature differences, the experimentally observed perceived intensity of TGI is compared with the neuronal activity of pain-sensitive HPC nerve fibers. The simulation results show a monotonically increasing relationship between the temperature differences and the neuronal activity of the HPC nerve fibers. Moreover, a similar monotonically increasing relationship is experimentally observed between temperature differences and the perceived TGI intensity. This shows the potential comparison of TGI pain intensity observed through the experimental study with the neuronal activity predicted through the model. The proposed model intends to bridge the theoretical understanding of the TGI and the experimental results obtained through psychophysics. Further studies in pain perception are needed to develop a more accurate version of the current model.

Keywords: thermal grill Illusion, computational modelling, simulation, psychophysics, haptics

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Authors: Boguslaw Schreyer

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In some types of wheeled robots it is important to secure starting acceleration and deceleration maxima while at the same time maintaining transversal stability. In this paper torque distribution between the front and rear wheels as well as the timing of torque application have been calculated. Both secure an optimum traction coefficient. This paper also identifies required input signals to a control unit, which controls the torque values and timing. Using a three dimensional, two mass model of a robot developed by the author a computer simulation was performed confirming the calculations presented in this paper. These calculations were also implemented and confirmed during military robot testing.

Keywords: robot dynamics, torque distribution, traction coefficient, wheeled robots

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

Procedia PDF Downloads 54