Search results for: finite element model/COMSOL multiphysics

Authors: Satish Kumar Dewangan, Santosh Kumar Senapati

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The present work focuses on the investigation of the effect of non-Newtonian behavior on the oil-water stratified flow in a horizontal channel using ANSYS Fluent. Coupled level set and volume of fluid (CLSVOF) has been used to capture the evolving interface assuming unsteady, coaxial flow with constant fluid properties. The diametric variation of oil volume fraction, mixture velocity, total pressure and pressure gradient has been studied. Non-Newtonian behavior of oil has been represented by the power law model in order to investigate the effect of flow behavior index. Stratified flow pattern tends to assume dispersed flow pattern with the change in the behavior of oil to non-Newtonian. The pressure gradient is found to be very much sensitive to the flow behavior index. The findings could be useful in designing the transportation pipe line in petroleum industries.

Keywords: oil-water stratified flow, horizontal channel, CLSVOF, non–Newtonian behaviour.

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Authors: Safia Akram

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In this article, the effects of peristaltic transport with double-diffusive convection in nanofluids through an asymmetric channel with different waveforms is presented. Mathematical modelling for two-dimensional and two directional flows of a Jeffrey fluid model along with double-diffusive convection in nanofluids are given. Exact solutions are obtained for nanoparticle fraction field, concentration field, temperature field, stream functions, pressure gradient and pressure rise in terms of axial and transverse coordinates under the restrictions of long wavelength and low Reynolds number. With the help of computational and graphical results the effects of Brownian motion, thermophoresis, Dufour, Soret, and Grashof numbers (thermal, concentration, nanoparticles) on peristaltic flow patterns with double-diffusive convection are discussed.

Keywords: nanofluid particles, peristaltic flow, Jeffrey fluid, magnetic field, asymmetric channel, different waveforms

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Authors: Koirala Abarodh, Maghaiya Ujjwal, Guragain Phani Raj

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This analysis focuses on defining the spectrum evaluation model for telecom operators in terms of total cost of ownership (TCO). A quantitative approach for specific case analysis research methodology was used for identifying the results. Specific input parameters like target User experience, year on year traffic growth, capacity site limit per year, target additional spectrum type, bandwidth, spectrum efficiency, UE penetration have been used for the spectrum evaluation process and desired outputs in terms of the number of sites, capex in USD and required spectrum bandwidth have been calculated. Furthermore, this study gives a comparison of capex investment for target growth with and without addition spectrum. As a result, the combination of additional spectrum bands of 700 and 2600 MHz has a better evaluation in terms of TCO and performance. It is our recommendation to use these bands for expansion rather than expansion in the current 1800 and 2100 bands.

Keywords: spectrum, capex planning, case study methodology, TCO

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Authors: M. Adjabi, A. Amiar, P. O. Logerais

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Flexible Alternative Current Systems Transmission (FACTS) are used since nearly four decades and present very good dynamic performances. The purpose of this work is to study the behavior of a system where Static Compensator (STATCOM) is located at the midpoint of a transmission line which is the idea of the project functioning in disturbed modes with various levels of load. The studied model and starting from the analysis of various alternatives will lead to the checking of the aptitude of the STATCOM to maintain the voltage plan and to improve the power flow in electro-energetic system which is the east region of Algerian 400 kV transmission network. The steady state performance of STATCOM’s controller is analyzed through computer simulations with Matlab/Simulink program. The simulation results have demonstrated that STATCOM can be effectively applied in power transmission systems to solve the problems of poor dynamic performance and voltage regulation.

Keywords: STATCOM, reactive power, power flow, voltage plan, Algerian network

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Authors: M. Adjabi, A. Amiar, P. O. Logerais

Abstract:

Flexible Alternative Current Systems Transmission (FACTS) are used since nearly four decades and present very good dynamic performances. The purpose of this work is to study the behavior of a system where Static Compensator (STATCOM) is located at the midpoint of a transmission line which is the idea of the project functioning in disturbed modes with various levels of load. The studied model and starting from the analysis of various alternatives will lead to the checking of the aptitude of the STATCOM to maintain the voltage plan and to improve the power flow in electro-energetic system which is the east region of Algerian 400 kV transmission network. The steady state performance of STATCOM’s controller is analyzed through computer simulations with Matlab/Simulink program. The simulation results have demonstrated that STATCOM can be effectively applied in power transmission systems to solve the problems of poor dynamic performance and voltage regulation.

Keywords: STATCOM, reactive power, power flow, voltage plan, Algerian network

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Tanu Aneja, Harsha Malaviya

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Capturing pose information in cricket shots poses several challenges, such as low-resolution videos, noisy data, and joint occlusions caused by the nature of the shots. In response to these challenges, we propose a CondDGConv-based framework specifically for cricket shot prediction. By analyzing the spatial-temporal relationships in batsman shot sequences from an annotated 2D cricket dataset, our model achieves a 97% accuracy in predicting shot types. This performance is made possible by conditioning the graph network on batsman 2D poses, allowing for precise prediction of shot outcomes based on pose dynamics. Our approach highlights the potential for enhancing shot prediction in cricket analytics, offering a robust solution for overcoming pose-related challenges in sports analysis.

Keywords: action recognition, cricket. sports video analytics, computer vision, graph convolutional networks

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Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: Asad Naeem, Jinkoo Kim

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This research proposes a self-centering passive damping system consisting of a spring viscous damper linked with a preloaded tendon. The seismic performance of the spring viscous damper is evaluated by pseudo-dynamic tests, and the results are used for the formulation of an analytical model of the damper in the structural analysis program. The shaking table tests of a two-story steel frame installed with the proposed damping system are carried out using five different earthquake records. The results from the shaking table tests are verified by numerical simulation of the retrofitted structure. The results obtained from experiments and numerical simulations demonstrate that the proposed damping system with self-centering capability is effective in reducing earthquake-induced displacement and member forces.

Keywords: seismic retrofit, spring viscous damper, shaking table test, earthquake resistant structures

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Authors: M. Shahina, K. Fakruddin, C. M. Subhan, S. Rangappa

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In this work, two mixtures with equal concentrations of 1) 4ꞌ-(6-(4-(pentylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(hexyloxy) benzylidene) amino) phenyl 4-butoxy benzoate and 2) 4ꞌ - (6-(4-(hexylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(octyloxy) benzylidene) amino) phenyl 4-butoxy benzoate, have been prepared. The transition temperature and optical texture are observed by using thermal microscopy. Density and birefringence studies are carried out on the above liquid crystalline mixtures. Using density and refractive indices data, the molecular polarizabilities are evaluated by using well-known Vuks and Neugebauer models. The molecular polarizability is also evaluated theoretically by Lippincott δ function model. The results reveal that the polarizability values are same in both experimental and theoretical methods.

Keywords: liquid crystals, optical textures, transition temperature, birefringence, polarizability

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Authors: Huey-Wen Chou, Shuo-Heng Liang

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This study focuses on studying college students’ multitasking with cellphones/laptops during lectures. In-class multitasking behavior is defined as the activities students engaged that are irrelevant to learning. This study aims to understand if students' learning engagement affects students' multitasking as well as to investigate the causes or motivations that contribute to the occurrence of multitasking behavior. Survey data were collected and analyzed by PLS method and multiple regression to test the research model and hypothesis. Major results include: 1. Students' multitasking motivation positively predicts students’ in-class multitasking. 2. Factors affecting multitasking in class, including efficiency, entertainment and social needs, significantly impact on multitasking. 3. Polychronic personality traits will positively predict students’ multitasking. 4. Students' classroom learning engagement negatively predicts multitasking. 5. Course attributes negatively predict student learning engagement and positively predict student multitasking.

Keywords: engagement, monochronic personality, multitasking, learning, personality traits

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Authors: G. Carrero, C. Contreras, M. J. Hendzel

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Linker histones or histones H1 are highly mobile nuclear proteins that regulate the organization of chromatin and limit DNA accessibility by binding to the chromatin structure (DNA and associated proteins). It is known that this binding process is driven by both slow (strong binding) and rapid (weak binding) interactions. However, the exact binding mechanism has not been fully described. Moreover, the existing models only account for one type of bound population that does not distinguish explicitly between the weakly and strongly bound proteins. Thus, we propose different systems of reaction-diffusion equations to describe explicitly the rapid and slow interactions during a FRAP (Fluorescence Recovery After Photobleaching) experiment. We perform a model comparison analysis to characterize the binding mechanism of histone H1 and provide new meaningful biophysical information on the kinetics of histone H1.

Keywords: FRAP (Fluorescence Recovery After Photobleaching), histone H1, histone H1 binding kinetics, linker histone, reaction-diffusion equation

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Meihua Fang, Yipan Guo, Tao Fei, Pengyu Tian

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Space plasma caused spacecraft surface charging is the major space environment hazard. Particle in cell (PIC) method can be used to simulate the interaction between space plasma and spacecraft. It was proved that surface charging level of spacecraft in Jupiter’s orbits was high for its’ electron-heavy plasma environment. In this paper, Jovian plasma environment is modeled and surface charging analysis is carried out by PIC based software Spacecraft Plasma Interaction System (SPIS). The results show that the spacecraft charging potentials exceed 1000V at 2Rj, 15Rj and 25Rj polar orbits in the dark side at worst case plasma model. Furthermore, the simulation results indicate that the large Jovian magnetic field increases the surface charging level for secondary electron gyration.

Keywords: Jupiter, PIC, space plasma, surface charging

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Moustafa Odah

Abstract:

Organic Agriculture is a new and sustainable agricultural system that depends on the use of organic materials from within the farm resulting from crop residues and animal husbandry and the cultivation of leguminous crops, away from the use of chemicals in fertilization or pest resistance, which leads to the production of safe, clean and healthy food products with nutritional value high and free of chemicals enhance food security; it is also an agricultural model preserve natural resources by improving the fertility and soil characteristics, and enhance biodiversity and biological cycles; additionally, they preserve the environment from pollution, which makes it play an important role in providing food needs of the present generations and the preservation of the rights of the coming generations to achieve sustainable development.

Keywords: organic agriculture, food security and achieving sustainable development, fertilization or pest resistance, crop residues and animal husbandry and the cultivation of leguminous crops

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Authors: Faris A. Uriayer, Mehtab Alam

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The concept of using a hybrid composite by combining two or more different materials to produce bilinear stress–strain behaviour has become a subject of interest. Having studied the mechanical properties of steel-CFRP specimens (CFRP Laminate Sandwiched between Mild Steel Strips), full size steel-CFRP composite reinforcement were fabricated and used as a new reinforcing material inside beams in lieu of traditional steel bars. Four beams, three beams reinforced with steel-CFRP composite reinforcement and one beam reinforced with traditional steel bars were cast, cured and tested under quasi-static loading. The flexural test results of the beams reinforced with this composite reinforcement showed that the beams with steel-CFRP composite reinforcement had comparable flexural strength and flexural ductility with beams reinforced with traditional steel bars.

Keywords: CFRP laminate, steel strip, flexural behaviour, modified model, concrete beam

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Authors: Sachin Kamble, Shradha Gawankar

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This paper presents the findings of successful implementation of Business Process Reengineering (BPR) of cement dispatch activities in a cement manufacturing plant located in India. Simulation model was developed for the purpose of identifying and analyzing the areas for improvement. The company was facing a problem of low throughput rate and subsequent forced stoppages of the plant leading to a high production loss of 15000MT per month. It was found from the study that the present systems and procedures related to the in-plant logistics plant required significant changes. The major recommendations included process improvement at the entry gate, reducing the cycle time at the security gate and installation of an additional weigh bridge. This paper demonstrates how BPR can be implemented for improving the in-plant logistics process. Various recommendations helped the plant to increase its throughput by 14%.

Keywords: in-plant logistics, cement logistics, simulation modelling, business process re-engineering, supply chain management

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Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

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New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

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Authors: Liu Yi, Bao Liyong

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Aiming at the problem of low efficiency of pipelined scheduling in periodic query-qualified service, this paper proposes a system service resource scheduling strategy with parallel optimized qualified service polling control. The paper constructs the polling queuing system and its mathematical model; firstly, the first-order and second-order characteristic parameter equations are obtained by partial derivation of the probability mother function of the system state variables, and the complete mathematical, analytical expressions of each system parameter are deduced after the joint solution. The simulation experimental results are consistent with the theoretical calculated values. The system performance analysis shows that the average captain and average period of the system have been greatly improved, which can better adapt to the service demand of delay-sensitive data in the dense data environment.

Keywords: polling, parallel scheduling, mean queue length, average cycle time

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Authors: Moomen Chaari, Wolfgang Ecker, Thomas Kruse, Bogdan-Andrei Tabacaru

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In our daily life, we frequently interact with complex systems which facilitate our mobility, enhance our access to information, and sometimes help us recover from illnesses or diseases. The reliance on these systems is motivated by the established evaluation and assessment procedures which are performed during the different phases of the design and manufacturing flow. Such procedures are aimed to qualify the system’s delivered services with respect to their availability, reliability, safety, and other properties generally referred to as dependability attributes. In this paper, we propose a metamodel based generic characterization of dependability concepts and describe an automation methodology to customize this characterization to different standards and contexts. When integrated in concrete design and verification environments, the proposed methodology promotes the reuse of already available dependability assessment tools and reduces the costs and the efforts required to create consistent and efficient artefacts for fault injection or error simulation.

Keywords: dependability analysis, model-driven development, metamodeling, code generation

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Authors: Ahmed Amine Hachicha

Abstract:

Temperature effect on the performance of a photovoltaic module is one of the main concern that face this renewable energy, especially in the hot arid region, e.g United Arab Emirates. Overheating of the PV modules reduces the open circuit voltage and the efficiency of the modules dramatically. In this work, water cooling is developed to enhance the performance of PV modules. Different scenarios are tested under UAE weather conditions: front, back and double cooling. A spraying system is used for the front cooling whether a direct contact water system is used for the back cooling. The experimental results are compared to a non-cooling module and the performance of the PV module is determined for different situations. A mathematical model is presented to estimate the theoretical performance and validate the experimental results with and without cooling. The experimental results show that the front cooling is more effective than the back cooling and may decrease the temperature of the PV module significantly.

Keywords: PV cooling, solar energy, cooling methods, electrical efficiency, temperature effect

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Authors: Saurav Kumar Suman, P. Karthigayani

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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

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The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

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Authors: Slim Chokri

Abstract:

Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

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This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Preshanthan Moodley

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This study compares two different pretreatments for sugarcane leaf waste (SLW): steam salt-alkali (SSA) and microwave salt-alkali (MSA). The two pretreatment types were modelled, optimized, and validated with R² > 0.97. Reducing sugar yields of 1.21g/g were obtained with optimized SSA pretreatment using 1.73M ZnCl₂, 1.36M NaOH and 9.69% solid loading, and 1.17g/g with optimized MSA pretreatment using 1.67M ZnCl₂, 1.52M NaOH at 400W for 10min. A lower pretreatment time (10min) was required for the MSA model (83% lower). The structure of pretreated SLW was assessed using scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR). The optimized SSA and MSA models showed lignin removal of 80.5 and 73% respectively. The MSA pretreatment was further examined on sorghum leaves and Napier grass and showed yield improvements of 1.9- and 2.8-fold compared to recent reports. The developed pretreatment methods demonstrated high efficiency at enhancing enzymatic hydrolysis on various lignocellulosic substrates.

Keywords: lignocellulosic biomass, pretreatment, salt, sugarcane leaves

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Authors: Rodrigo Calili, Anna Carolina Sermarini, João Henrique Azevedo, Vanessa Cardoso de Albuquerque, Felipe Gonçalves, Gilberto Jannuzzi

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The diffusion of Distributed Energy Resources (DER) has caused structural changes in the relationship between consumers and electrical systems. The Photovoltaic Distributed Generation (PVDG), in particular, is an essential strategy for achieving the 2030 Agenda goals, especially SDG 7 and SDG 13. However, it is observed that most projects involving this technology in Brazil are restricted to the wealthiest classes of society, not yet reaching the low-income population, aligned with theories of energy justice. Considering the research for energy equality, one of the policies adopted by governments is the social electricity tariff (SET), which provides discounts on energy tariffs/bills. However, just granting this benefit may not be effective, and it is possible to merge it with DER technologies, such as the PVDG. Thus, this work aims to evaluate the economic viability of the policy to replace the social electricity tariff (the current policy aimed at the low-income population in Brazil) by PVDG projects. To this end, a proprietary methodology was developed that included: mapping the stakeholders, identifying critical variables, simulating policy options, and carrying out an analysis in the Brazilian context. The simulation answered two key questions: in which municipalities low-income consumers would have lower bills with PVDG compared to SET; which consumers in a given city would have increased subsidies, which are now provided for solar energy in Brazil and for the social tariff. An economic model was created for verifying the feasibility of the proposed policy in each municipality in the country, considering geographic issues (tariff of a particular distribution utility, radiation from a specific location, etc.). To validate these results, four sensitivity analyzes were performed: variation of the simultaneity factor between generation and consumption, variation of the tariff readjustment rate, zeroing CAPEX, and exemption from state tax. The behind-the-meter modality of generation proved to be more promising than the construction of a shared plant. However, although the behind-the-meter modality presents better results than the shared plant, there is a greater complexity in adopting this modality due to issues related to the infrastructure of the most vulnerable communities (e.g., precarious electrical networks, need to reinforce roofs). Considering the shared power plant modality, many opportunities are still envisaged since the risk of investing in such a policy can be mitigated. Furthermore, this modality can be an alternative due to the mitigation of the risk of default, as it allows greater control of users and facilitates the process of operation and maintenance. Finally, it was also found, that in some regions of Brazil, the continuity of the SET presents more economic benefits than its replacement by PVDG. However, the proposed policy offers many opportunities. For future works, the model may include other parameters, such as cost with low-income populations’ engagement, and business risk. In addition, other renewable sources of distributed generation can be studied for this purpose.

Keywords: low income, subsidy policy, distributed energy resources, energy justice

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

Procedia PDF Downloads 277