Search results for: Boundary-fitted nested grid model

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Jay N. Vyas, Sachin Daxini

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Numerical simulation techniques are widely used now in product development and testing instead of expensive, time-consuming and sometimes dangerous laboratory experiments. Numerous numerical methods are available for performing simulation of physical problems of different engineering fields. Grid based methods, like Finite Element Method, are extensively used in performing various kinds of static, dynamic, structural and non-structural analysis during product development phase. Drawbacks of grid based methods in terms of discontinuous secondary field variable, dealing fracture mechanics and large deformation problems led to development of a relatively a new class of numerical simulation techniques in last few years, which are popular as Meshless methods or Meshfree Methods. Meshless Methods are expected to be more adaptive and flexible than Finite Element Method because domain descretization in Meshless Method requires only nodes. Present paper introduces Meshless Methods and differentiates it with Finite Element Method in terms of following aspects: Shape functions used, role of weight function, techniques to impose essential boundary conditions, integration techniques for discrete system equations, convergence rate, accuracy of solution and computational effort. Capabilities, benefits and limitations of Meshless Methods are discussed and concluded at the end of paper.

Keywords: numerical simulation, Grid-based methods, Finite Element Method, Meshless Methods

Procedia PDF Downloads 369

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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Authors: Antonio Pizzarello, Oris Friesen

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Networks, such as the electric power grid, must demonstrate exemplary performance and integrity. Integrity depends on the quality of both the system design model and the deployed software. Integrity of the deployed software is key, for both the original versions and the many that occur throughout numerous maintenance activity. Current software engineering technology and practice do not produce adequate integrity. Distributed systems utilize networks where each node is an independent computer system. The connections between them is realized via a network that is normally redundantly connected to guarantee the presence of a path between two nodes in the case of failure of some branch. Furthermore, at each node, there is software which may fail. Self-stabilizing protocols are usually present that recognize failure in the network and perform a repair action that will bring the node back to a correct state. These protocols first introduced by E. W. Dijkstra are currently present in almost all Ethernets. Super stabilization protocols capable of reacting to a change in the network topology due to the removal or addition of a branch in the network are less common but are theoretically defined and available. This paper describes how to use the Software Integrity Assessment (SIA) methodology to analyze self-stabilizing software. SIA is based on the UNITY formalism for parallel and distributed programming, which allows the analysis of code for verifying the progress property p leads-to q that describes the progress of all computations starting in a state satisfying p to a state satisfying q via the execution of one or more system modules. As opposed to demonstrably inadequate test and evaluation methods SIA allows the analysis and verification of any network self-stabilizing software as well as any other software that is designed to recover from failure without external intervention of maintenance personnel. The model to be analyzed is obtained by automatic translation of the system code to a transition system that is based on the use of the weakest precondition.

Keywords: network, power grid, self-stabilization, software integrity assessment, UNITY, weakest precondition

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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Authors: Majed Ahmadi

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In recent years, the high penetration of different types of renewable energy sources (RESs) has affected most of the available strategies. The main motivations behind the high penetration of RESs are clean energy, modular system and easy installation. Among different types of RESs, wind turbine (WT) is an interesting choice referring to the availability of wind in almost any area. The new technologies of WT can provide energy from residential applications to wide grid connected applications. Regarding the WT, advantages such as reducing the dependence on fossil fuels and enhancing the independence and flexibility of large power grid are the most prominent. Nevertheless, the high volatile nature of wind speed injects much uncertainty in the grid that if not managed optimally can put the analyses far from the reality.the aim of this project is scrutiny and to offer proper ways for renewing distribution networks with envisage the effects of wind power plants and uncertainties related to distribution systems including wind power generating plants output rate and consumers consuming rate and also decrease the incidents of the whole network losses, amount of pollution, voltage refraction and cost extent.to solve this problem we use dual point estimate method.And algorithm used in this paper is reformed bat algorithm, which will be under exact research furthermore the results.

Keywords: order renewal, wind turbines, bat algorithm, outspread production, uncertainty

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Yehya Abdellatif, Ahmed Alsalaymeh, Iyad Muslih, Ali Alshduifat

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Photovoltaic (PV) power generation systems, mainly small scale, are rapidly being deployed in Jordan. The impact of these systems on the grid has not been studied or analyzed. These systems can cause many technical problems such as reverse power flows and voltage rises in distribution feeders, and real and reactive power transients that affect the operation of the transmission system. To fully understand and address these problems, extensive research, simulation, and case studies are required. To this end, this paper studies the cloud shadow effect on the power generation of a ground mounted PV system installed at the test field of the Renewable Energy Center at the Applied Science University.

Keywords: photovoltaic, cloud effect, MPPT, power transients

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Authors: Marwa M. Ibrahim

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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) off-grid system supplying a small remote gathering of four families using the HOMER software package. The second objective is to study the effect of wind energy system on the cost of generated electricity considering the cost of reducing CO₂ emissions as external benefit of wind turbines, no pollutant emission through the operational phase. The system consists of a small wind turbine, battery storage, and diesel generator. The electrical energy is to cater to the basic needs for which the daily load pattern is estimated at 8 kW peak. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for the selected site in Egypt. Using HOMER software, the simulation results shows that W/D/B systems are economical for the assumed community site as the price of generated electricity is about 0.285 $/kWh, without taking external benefits into considerations and 0.221 if CO₂ emissions taken into consideration W/D/B systems are more economical than alone diesel system as the COE is 0.432 $/kWh for diesel alone.

Keywords: renewable energy, hybrid energy system, on-off grid system, simulation, optimization and environmental impacts

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Authors: Mohamad Mohsen Homayouni, Niloofar Taghipour, Ahmad Reza Memar, Niloofar Khalaji, Hamed Kiani, Seyyed Javad Seyyed Tabaei

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Background and Objective: Cryptosporidium is a coccidian protozoan parasite; its oocysts in surface water are a global health problem. Due to the low number of parasites in the water resources and the lack of laboratory culture, rapid and sensitive method for detection of the organism in the water resources is necessarily required. We applied modified acid-fast staining and PCR for the detection of the Cryptosporidium spp. and analysed the genotypes in 55 samples collected from surface water. Methods: Over a period of nine months, 55 surface water samples were collected from the five rivers in Tehran, Iran. The samples were filtered by using cellulose acetate membrane filters. By acid fast method, initial identification of Cryptosporidium oocyst were carried out on surface water samples. Then, nested PCR assay was designed for the specific amplification and analysed the genotypes. Results: Modified Ziehl-Neelsen method revealed 5–20 Cryptosporidium oocysts detected per 10 Liter. Five out of the 55 (9.09%) surface water samples were found positive for Cryptosporidium spp. by Ziehl-Neelsen test and seven (12.7%) were found positive by nested PCR. The staining results were consistent with PCR. Seven Cryptosporidium PCR products were successfully sequenced and five gp60 subtypes were detected. Our finding of gp60 gene revealed that all of the positive isolates were Cryptosporidium parvum and belonged to subtype families IIa and IId. Conclusion: Our investigations were showed that collection of water samples were contaminated by Cryptosporidium, with potential hazards for the significant health problem. This study provides the first report on detection and genotyping of Cryptosporidium species from surface water samples in Iran, and its result confirmed the low clinical incidence of this parasite on the community.

Keywords: Cryptosporidium spp., membrane filtration, subtype, surface water, Iran

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: Sudarshan Chalise, Athula Naranpanawa

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This paper attempts to investigate the viability of cropland re-allocation as an adaptation strategy to minimise the economy-wide costs of climate change on agriculture. Nepal makes an interesting case study as it is one of the most vulnerable agricultural economies within South Asia. This paper develops a comparative static multi-household Computable General Equilibrium (CGE) model for Nepal with a nested set of Constant Elasticity of Transformation (CET) functional forms to model the allocation of land within different agricultural sectors. Land transformation elasticities in these CET functions are allowed to reflect the ease of switching from one crop to another based on their agronomic characteristics. The results suggest that, in the long run, farmers in Nepal tend to allocate land to crops that are comparatively less impacted by climate change, such as paddy, thereby minimizing the economy-wide impacts of climate change. Furthermore, the results reveal that land re-allocation tends to reduce the income disparity among different household groups by significantly moderating the income losses of rural marginal farmers. Therefore, it is suggested that policy makers in Nepal should prioritise schemes such as providing climate-smart paddy varieties (i.e., those that are resistant to heat, drought and floods) to farmers, subsidising fertilizers, improving agronomic practices, and educating farmers to switch from crops that are highly impacted by climate change to those that are not, such as paddy.

Keywords: climate change, general equilibrium, land re-allocation, nepalese agriculture

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Authors: Hninn Thiri Naing

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In Myanmar, there are many regions that are far away from the national grid. For these areas, isolated regional micro-grids are one of the solutions. The study area in this paper is also operating in such way. The main difficulty in such regions is the high cost of electrical energy. This paper will be approached to cost-effective or cost-optimization by energy planning with renewable energy resources and natural gas. Micro-grid will be set up for performance in the Dawei region since it is economic zone in lower Myanmar and so far from national grids. The required metrological and geographical data collections are done. Currently, the status is electric unit rate is higher than the other. For microgrid planning and optimization, Homer Pro-software is employed in this research.

Keywords: energy planning, renewable energy, homer pro, cost of energy

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Authors: Vinay C. Doranalu, Amba Shetty

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In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.

Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric

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Authors: Réka Sárközi, Péter Iványi, Attila B. Széll

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The aim of this paper is to present the adaptation of the dome construction tool for formex algebra to the parametric design software Grasshopper. Formex algebra is a mathematical system, primarily used for planning structural systems such like truss-grid domes and vaults, together with the programming language Formian. The goal of the research is to allow architects to plan truss-grid structures easily with parametric design tools based on the versatile formex algebra mathematical system. To produce regular structures, coordinate system transformations are used and the dome structures are defined in spherical coordinate system. Owing to the abilities of the parametric design software, it is possible to apply further modifications on the structures and gain special forms. The paper covers the basic dome types, and also additional dome-based structures using special coordinate-system solutions based on spherical coordinate systems. It also contains additional structural possibilities like making double layer grids in all geometry forms. The adaptation of formex algebra and the parametric workflow of Grasshopper together give the possibility of quick and easy design and optimization of special truss-grid domes.

Keywords: parametric design, structural morphology, space structures, spherical coordinate system

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Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: B. Casper

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The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

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Authors: Kawser Ahmed, K. Bousson, Milca F. Coelho

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4D flight trajectory optimization is one of the key ingredients to improve flight efficiency and to enhance the air traffic capacity in the current air traffic management (ATM). The present paper explores the iterative dynamic programming (IDP) as a potential numerical optimization method for 4D flight trajectory optimization. IDP is an iterative version of the Dynamic programming (DP) method. Due to the numerical framework, DP is very suitable to deal with nonlinear discrete dynamic systems. The 4D waypoint representation of the flight trajectory is similar to the discretization by a grid system; thus DP is a natural method to deal with the 4D flight trajectory optimization. However, the computational time and space complexity demanded by the DP is enormous due to the immense number of grid points required to find the optimum, which prevents the use of the DP in many practical high dimension problems. On the other hand, the IDP has shown potentials to deal successfully with high dimension optimal control problems even with a few numbers of grid points at each stage, which reduces the computational effort over the traditional DP approach. Although the IDP has been applied successfully in chemical engineering problems, IDP is yet to be validated in 4D flight trajectory optimization problems. In this paper, the IDP has been successfully used to generate minimum length 4D optimal trajectory avoiding any obstacle in its path, such as a no-fly zone or residential areas when flying in low altitude to reduce noise pollution.

Keywords: 4D waypoint navigation, iterative dynamic programming, obstacle avoidance, trajectory optimization

Procedia PDF Downloads 134

Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

Abstract:

Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: digital twin, distributed energy resources, remote terminal units, supervisory control and data acquisition system, smart recursive load flow

Procedia PDF Downloads 77

Authors: Olusola Ezekiel Abolarin, Gift E. Noah

Abstract:

This research work considered an innovative procedure to numerically approximate higher-order Initial value problems (IVP) of ordinary differential equations (ODE) using the Legendre polynomial as the basis function. The proposed method is a half-step, self-starting Block integrator employed to approximate fourth and fifth order IVPs without reduction to lower order. The method was developed through a collocation and interpolation approach. The basic properties of the method, such as convergence, consistency and stability, were well investigated. Several test problems were considered, and the results compared favorably with both exact solutions and other existing methods.

Keywords: initial value problem, ordinary differential equation, implicit off-grid block method, collocation, interpolation

Procedia PDF Downloads 53

Authors: Malika El Kyal, Ahmed Machmoum

Abstract:

We prove the superlinear convergence of asynchronous multi-splitting methods applied to differential equations. This study is based on the technique of nested sets. It permits to specify kind of the convergence in the asynchronous mode.The main characteristic of an asynchronous mode is that the local algorithm not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays to be substantial and unpredictable. Note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: parallel methods, asynchronous mode, multisplitting, ODE

Procedia PDF Downloads 502

Authors: Abdul-Rahman Al-Ali

Abstract:

As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

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Authors: Santhosh Kumat T., Priya E.

Abstract:

The control of a doubly fed induction generator by fuzzy is described. The active and reactive power can be controlled by rotor and grid side converters with fuzzy controller. The main objective is to maintain constant voltage and frequency at the output of the generator. However the Line Side Converter (LSC) can be controlled to supply up to 50% of the required reactive current. When the crowbar is not activated the DFIG can supply reactive power from the rotor side through the machine as well as through the LSC.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Side Converter (RSC), Grid Side Converter (GSC), Wind Energy Conversion Systems (WECS)

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Authors: Sania Maghsodloo, Sirus Mohammadi

Abstract:

Electric Vehicle (EV) technology is expected to take a major share in the light-vehicle market in the coming decades. Transportation electrification has become an important issue in recent decades and the large scale deployment of EVs has yet to be achieved. The smart coordination of EV demand addresses an improvement in the flexibility of power systems and reduces the costs of power system investment. The uncertainty in EV drivers’ behaviour is one of the main problems to solve to obtain an optimal integration of EVs into power systems Charging of EVs will put an extra burden on the distribution grid and in some cases adjustments will need to be made. The stochastic process of the driving pattern is done to make the outcome of the project more realistic. Based on the stochastic data, the optimization of charging plans is made.

Keywords: electric vehicles (PEVs), smart grid, Monticello, distribution system

Procedia PDF Downloads 533