Search results for: energy modeling techniques

Authors: Xue Wang, Liwei Fan

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Renewable energy technology innovation is an important way to realize the energy transformation. Our government has issued a series of policies to guide and support the development of renewable energy. The implementation of these policies will affect the further development, utilization and technological innovation of renewable energy. In this context, it is of great significance to systematically sort out and evaluate the renewable energy technology innovation policy for improving the existing policy system. Taking the 190 renewable energy technology innovation policies issued during 2005-2021 as a sample, from the perspectives of policy issuing departments and policy keywords, it uses text mining and content analysis methods to analyze the current situation of the policies and conduct a semantic network analysis to identify the core issuing departments and core policy topic words; A PMC (Policy Modeling Consistency) index model is built to quantitatively evaluate the selected policies, analyze the overall pros and cons of the policy through its PMC index, and reflect the PMC value of the model's secondary index The core departments publish policies and the performance of each dimension of the policies related to the core topic headings. The research results show that Renewable energy technology innovation policies focus on synergy between multiple departments, while the distribution of the issuers is uneven in terms of promulgation time; policies related to different topics have their own emphasis in terms of policy types, fields, functions, and support measures, but It still needs to be improved, such as the lack of policy forecasting and supervision functions, the lack of attention to product promotion, and the relatively single support measures. Finally, this research puts forward policy optimization suggestions in terms of promoting joint policy release, strengthening policy coherence and timeliness, enhancing the comprehensiveness of policy functions, and enriching incentive measures for renewable energy technology innovation.

Keywords: renewable energy technology innovation, content analysis, policy evaluation, PMC index model

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Authors: Abdelkarim Ait Brik, Abdelaziz Khoukh, Mustapha Jammali, Hamid Chaikhy

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The energy audit is the essential initial step to ensure a good definition of energy control actions. The in-depth study of the various energy-consuming equipments makes it possible to determine the actions and investments with best cost for the company. The analysis focuses on the energy consumption of production equipment and utilities (lighting, heating, air conditioning, ventilation, transport). Successful implementation of this approach requires, however, to take into account a number of prerequisites. This paper proposes a number of useful recommendations concerning the energy audit in order to achieve better results, and a case study concerning the lighting audit of a Moroccan company by showing the gains that can be made through this audit.

Keywords: energy audit, energy diagnosis, consumption, electricity, energy efficiency, lighting audit

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Authors: Madikeri Rohit

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As energy efficiency is the key concern in many aircraft manufacturing companies regenerative braking is a technique using which energy lost due to friction while braking can be regained. In the operation of an aircraft, significant energy is lost during deceleration or braking which occurs during its landing phase. This problem can be overcome using Regenerative Breaking System (RBS) in landing gear. The major problem faced is regarding the batteries and the overall efficiency gained in competence with the added weight. As the amount of energy required to store is huge we need batteries with high capacity for storage. Another obstacle by using high capacity batteries is the added weight which undermines the efficiency obtained using RBS. An approach to this problem is to either use the obtained energy immediately without storage or to store in other forms such as mechanical, pneumatic and hydraulic. Problem faced with mechanical systems is the weight of the flywheel needed to obtain required efficiency. Pneumatic and hydraulic systems are a better option at present. Using hydraulic systems for storing energy is efficient as it integrates into the overall hydraulic system present in the aircraft. Another obstacle is faced with the redundancy of this system. Conventional braking must be used along with RBS in order to provide redundancy. Major benefits obtained using RBS is with the help of the energy obtained during landing which can be used of engine less taxing. This reduces fuel consumption as well as noise and air pollution. Another added benefit of using RBS is to provide electrical supply to lighting systems, cabin pressurization system and can be used for emergency power supply in case of electric failure. This paper discusses about using RBS in landing gear, problems, prospects and new techniques being pursued to improve RBS.

Keywords: regenerative braking, types of energy conversion, landing gear, energy storage

Procedia PDF Downloads 240

Authors: Lina Wu, Jia Liu, Ye Li

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The goal of this project is to investigate constant properties (called the Liouville-type Problem) for a p-stable map as a local or global minimum of a p-energy functional where the domain is a Euclidean space and the target space is a closed half-ellipsoid. The First and Second Variation Formulas for a p-energy functional has been applied in the Calculus Variation Method as computation techniques. Stokes’ Theorem, Cauchy-Schwarz Inequality, Hardy-Sobolev type Inequalities, and the Bochner Formula as estimation techniques have been used to estimate the lower bound and the upper bound of the derived p-Harmonic Stability Inequality. One challenging point in this project is to construct a family of variation maps such that the images of variation maps must be guaranteed in a closed half-ellipsoid. The other challenging point is to find a contradiction between the lower bound and the upper bound in an analysis of p-Harmonic Stability Inequality when a p-energy minimizing map is not constant. Therefore, the possibility of a non-constant p-energy minimizing map has been ruled out and the constant property for a p-energy minimizing map has been obtained. Our research finding is to explore the constant property for a p-stable map from a Euclidean space into a closed half-ellipsoid in a certain range of p. The certain range of p is determined by the dimension values of a Euclidean space (the domain) and an ellipsoid (the target space). The certain range of p is also bounded by the curvature values on an ellipsoid (that is, the ratio of the longest axis to the shortest axis). Regarding Liouville-type results for a p-stable map, our research finding on an ellipsoid is a generalization of mathematicians’ results on a sphere. Our result is also an extension of mathematicians’ Liouville-type results from a special ellipsoid with only one parameter to any ellipsoid with (n+1) parameters in the general setting.

Keywords: Bochner formula, Calculus Stokes' Theorem, Cauchy-Schwarz Inequality, first and second variation formulas, Liouville-type problem, p-harmonic map

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Authors: Bahram Fathi, Seyedhossein Sajadifar, Naser Khiabani

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Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as byproducts of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 12 OPEC countries and the results obtained are presented.

Keywords: energy efficiency, undesirable outputs, data envelopment analysis

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Authors: Sumit Kumar, Sunil Kumar, Chandan Deep Singh

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This paper presents modeling and simulation of flexible robot in an underwater environment. The underwater environment completely contrasts with ground or space environment. The robot in an underwater situation is subjected to various dynamic forces like buoyancy forces, hydrostatic and hydrodynamic forces. The underwater robot is modeled as Rayleigh beam. The developed model further allows estimating the deflection of tip in two directions. The complete dynamics of the underwater robot is analyzed, which is the main focus of this investigation. The control of robot trajectory is not discussed in this paper. Simulation is performed using Symbol Shakti software.

Keywords: bond graph modeling, dynamics. modeling, rayleigh beam, underwater robot

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Authors: Elhadj Bounadja, Mohand Oulhadj Mahmoudi, Abdelkader Djahbar, Zinelaabidine Boudjema

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In this paper we present a novel fuzzy second-order sliding mode control (FSOSMC) for wind energy conversion system based on a doubly-fed induction generator (DFIG). The proposed control strategy combines a fuzzy logic and a second-order sliding mode for the DFIG control. This strategy presents attractive features such as chattering-free, compared to the conventional first and second order sliding mode techniques. The use of this method provides very satisfactory performance for the DFIG control. The overall strategy has been validated on a 1.5-MW wind turbine driven a DFIG using the Matlab/Simulink.

Keywords: doubly fed induction generator, fuzzy second-order sliding mode controller, wind energy

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Authors: Yi Jin, Xu Tang, Cuiyang Feng

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The ‘11th five-year’ and ‘12th five-year’ plans have clearly put forward to strictly control the total amount and intensity of energy and water consumption. The synergy effect of energy and water has rarely been considered in the process of energy and water saving in China, where its contribution cannot be maximized. Energy sectors consume large amounts of energy and water when producing massive energy, which makes them both energy and water intensive. Therefore, the synergy effect in these sectors is significant. This paper assesses and optimizes the synergy effect in three energy sectors under the background of promoting energy and water saving. Results show that: From the perspective of critical path, chemical industry, mining and processing of non-metal ores and smelting and pressing of metals are coupling points in the process of energy and water flowing to energy sectors, in which the implementation of energy and water saving policies can bring significant synergy effect. Multi-objective optimization shows that increasing efforts on input restructuring can effectively improve synergy effects; relatively large synergetic energy saving and little water saving are obtained after solely reducing the energy and water intensity of coupling sectors. By optimizing the input structure of sectors, especially the coupling sectors, the synergy effect of energy and water saving can be improved in energy sectors under the premise of keeping economy running stably.

Keywords: critical path, energy sector, multi-objective optimization, synergy effect, water

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Authors: Hoa Thi Hoang, Stephan Sass, Michael U. Kumke

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Concanavalin A (conA) is a protein has been widely used in sensor system based on its specific binding to α-D-Glucose or α-D-Manose. For glucose sensor using conA, either fluoresence based techniques with intensity based or lifetime based are used. In this research, liposomes made from phospholipids were used as a biomimetic membrane system. In a first step, novel building blocks containing perylene labeled glucose units were added to the system and used to decorate the surface of the liposomes. Upon the binding between rhodamine labeled con A to the glucose units at the biomimetic membrane surface, a Förster resonance energy transfer system can be formed which combines unique fluorescence properties of perylene (e.g., high fluorescence quantum yield, no triplet formation) and its high hydrophobicity for efficient anchoring in membranes to form a novel probe for the investigation of sugar-driven binding reactions at biomimetic surfaces. Two glucose-labeled perylene derivatives were synthesized with different spacer length between the perylene and glucose unit in order to probe the binding of conA. The binding interaction was fully characterized by using high-end fluorescence techniques. Steady-state and time-resolved fluorescence techniques (e.g., fluorescence depolarization) in combination with single-molecule fluorescence spectroscopy techniques (fluorescence correlation spectroscopy, FCS) were used to monitor the interaction with conA. Base on the fluorescence depolarization, the rotational correlation times and the alteration in the diffusion coefficient (determined by FCS) the binding of the conA to the liposomes carrying the probe was studied. Moreover, single pair FRET experiments using pulsed interleaved excitation are used to characterize in detail the binding of conA to the liposome on a single molecule level avoiding averaging out effects.

Keywords: concanavalin A, FRET, sensor, biomimetic membrane

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Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra

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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.   

Keywords: ice-hockey, sprint, skating, power

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Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

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Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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Authors: Joon Sang Kang, Ming Ke, Yongjie Hu

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Controlling heat transfer and thermal properties of materials is important to many fields such as energy efficiency and thermal management of integrated circuits. Significant progress over the past decade has been made to improve material performance through structuring at the nanoscale, however a clear relationship between structure dimensions, interfaces, and thermal properties remains to be established. The main challenge comes from the unknown intrinsic spectral contribution from different phonons. Here, we describe our current progress on quantifying and controlling thermal spectra based on our recently developed technical approach using ultrafast optical spectroscopy. Our work brings further the promise of rational material design to achieve high performance through a synergistic experimental-modeling approach. This approach can be broadly applicable to a wide range of materials and energy systems. In particular, we demonstrate in-situ characterization and tunable thermal properties of 2D van der waals materials through ionic intercalations. The significant impacts of this research in improving the efficiency of thermal energy conversion and management will also be illustrated.

Keywords: energy, mean free path, nanoscale heat transfer, nanostructure, phonons, TDTR, thermoelectrics, 2D materials

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Authors: Sarah Abdourraziq, R. El Bachtiri

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Renewable energies have a major importance of Morocco's new energy strategy. The geographical location of the Kingdom promotes the development of the use of solar energy. The use of this energy reduces the dependence on imports of primary energy, meets the growing demand for water and electricity in remote areas encourages the deployment of a local industry in the renewable energy sector and Minimize carbon emissions. Indeed, given the importance of the radiation intensity received and the duration of the sunshine, the country can cover some of its solar energy needs. The use of solar energy to pump water is one of the most promising application, this technique represents a solution wherever the grid does not exist. In this paper, we will present a presentation of photovoltaic pumping system components, and the important solar pumping projects installed in Morocco to supply water from remote area.

Keywords: PV pumping system, Morocco, PV panel, renewable energy

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Authors: Pawel Sowa, Joachim Bargiel, Bogdan Mol, Katarzyna Luszcz

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The article raises the issue of the development of local renewable energy sources and the production of distributed energy in context of improving the reliability of the Polish Power System and the beneficial impact on local and national energy security. The paper refers to the current problems of local governments in the process of investment in the area of distributed energy projects, and discusses the issues of the future role and cooperation within the local power plants and distributed energy. Attention is paid to the local communities the chance to raise their own resources and management of energy fuels (biomass, wind, gas mining) and improving the local energy balance. The material presented takes the issue of the development of the energy potential of municipalities and future cooperation with professional energy. As an example, practical solutions used in one of the communes in Silesia.

Keywords: distributed generation, mini centers energy, renewable energy sources, reliability of supply of rural commune

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Authors: Slim Chokri

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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

Procedia PDF Downloads 417

Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

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This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

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Authors: Ammar Maziz, Mostapha Tarfaoui, Said Rechak

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The high mechanical performance of composite pipes can be adversely affected by their low resistance to impact loads. Loads in dynamic origin are dangerous and cause consequences on the operation of pipes because the damage is often not detected and can affect the structural integrity of composite pipes. In this work, an advanced 3-D finite element (FE) model, based on the use of intralaminar damage models was developed and used to predict damage under low-velocity impact. The performance of the numerical model is validated with the confrontation with the results of experimental tests. The results show that at low impact energy, the damage happens mainly by matrix cracking and delamination. The model capabilities to simulate the low-velocity impact events on the full-scale composite structures were proved.

Keywords: composite materials, low velocity impact, FEA, dynamic behavior, progressive damage modeling

Procedia PDF Downloads 146

Authors: J. Gochermann

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German energy market is under historical change. Turning-off the nuclear power plants and intensive subsidization of the renewable energies causes a paradigm change from big central energy production and distribution to more local structures, bringing the energy production near to the consumption. The formerly big energy market with only a few big energy plants and grid operating companies is changing into a disperse market with growing numbers of small and medium size companies (SME) generating new value-added products and services. This change in then energy market, in Germany called the “Energiewende”, inverts also the previous innovation system. Big power plants and large grids required also big operating companies. Innovations in the energy market focused mainly on big projects and complex energy technologies. Innovation in the new energy market structure is much more dispersed. Increasing number of SME is now able to develop energy production and storage technologies, smart technologies to control the grids, and numerous new energy related services. Innovation is now regional distributed, which is a remarkable problem for the old big energy companies. The paper will explain the change in the German energy market and the paradigm change as well as the consequences for the innovation structure in the German energy market. It will show examples how SME participate from this change and how innovation systems, as well for the big companies and for SME, can be adapted.

Keywords: changing energy markets, disperse innovation, new value-added products and services, SME

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Authors: Adavbiele Airewe Stephen

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Sustainable energy use is exploiting energy resources within acceptable levels of global resource depletion without destroying the ecological balance of an area. In the context of sustainability, the rush to quell the energy crisis of the fossil fuels of the 1970's by embarking on nuclear energy technology has now been seen as a disaster. In the circumstance, action (policy) suggested in this study to avoid future occurrence is exergy maximization/entropy generation minimization and the use is renewable energy technologies that are hybrid based. Thirty-two (32) selected hybrid renewable energy technologies were assessed with respect to their energetic efficiencies and entropy generation. The results indicated that determining which of the hybrid technologies is the most efficient process and sustainable is a matter of defining efficiency and knowing which of them possesses the minimum entropy generation.

Keywords: entropy, exergy, hybrid renewable energy technologies, sustainability

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Authors: Francisco Duarte, Adelino Ferreira, Paulo Fael

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With the growing need for alternative energy sources, research into energy harvesting technologies has increased considerably in recent years. The particular case of energy harvesting on road pavements is a very recent area of research, with different technologies having been developed in recent years. However, none of them have presented high conversion efficiencies nor technical or economic viability. This paper deals with the development of a mechanical system to implement on a road pavement energy harvesting electromechanical device, to transmit energy from the device surface to an electrical generator. The main goal is to quantify the energy harvesting, transmission and conversion efficiency of the proposed system and compare it with existing systems. Conclusions about the system’s efficiency are presented.

Keywords: road pavement, energy harvesting, energy conversion, system modelling

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers' equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile

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Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach using the Healthcare Multi-Agent System. The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are: The Behavioral Pattern Analysis (BPA) modeling methodology. The development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases, Healthcare Multi-Agent System

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Authors: Yuichi Miyamoto

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In regards to the energy sector in the modern period, two points were raised. First is a vast and growing energy demand, and second is an environmental impact associated with it. The enormous consumption of fossil fuel to the mobile unit is leading to its rapid depletion. Nuclear power is not the only problem. A modal shift that utilizes personal transporters and independent power, in order to realize a sustainable society, is very effective. The paper proposes that the world will continue to work on this. Energy of the future society, innovation in battery technology and the use of natural energy is a big key. And it is also necessary in order to save on energy consumption.

Keywords: natural energy, modal shift, personal transportation, battery

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: Kyoungjin Kim

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Nanoscale thermites such as the composite mixture of nano-sized aluminum and molybdenum trioxide powders possess several technical advantages such as much higher reaction rate and shorter ignition delay, when compared to the conventional energetic formulations made of micron-sized metal and oxidizer particles. In this study, the self-propagation of combustion wave in compacted pellets of nanoscale thermite composites is modeled and computationally investigated by utilizing the activation energy reduction of aluminum particles due to nanoscale particle sizes. The present computational model predicts the speed of combustion wave propagation which is good agreement with the corresponding experiments of thermite reaction. Also, several characteristics of thermite reaction in nanoscale composites are discussed including the ignition delay and combustion wave structures.

Keywords: nanoparticles, thermite reaction, combustion wave, numerical modeling

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Authors: H. Shokouhmand, M. Tajerian

Abstract:

At this paper velocity profile modeling and heat transfer in the micro heat pipes by using electrohydrodynamic (EHD) field at the transient regime have been studied. In the transient flow, one dimensional and two phase fluid flow and heat transfer for micro heat pipes with square cross section, have been studied. At this model Coulomb and dielectrophoretic forces are considered. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by numerical methods. Transient behavior of affecting parameters e.g. substrate temperature, velocity of coolant liquid, radius of curvature and coolant liquid pressure, has been verified. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. So, the time required to reach the steady state regime decreases from 16 seconds to 2.4 seconds after applying EHD field. Another result has been observed implicitly that by increasing the heat input the effect of EHD field became more significant. The numerical results of model predict the experimental results available in the literature successfully, and it has been observed there is a good agreement between them.

Keywords: micro heat pipe, transient modeling, electrohydrodynamics, capillary, meniscus

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Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

Procedia PDF Downloads 462