Search results for: energy models

Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: L. Grinis

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Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: open channel, physical modeling, baffles, turbulent flow

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Authors: Sihame Amakrane, Zineb Ouahdi, Mohammed Salah, Said Belaaouad

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\This research explores the efficacy of novel pyrimidine derivatives on bacterial strains such as Escherichia coli, Staphylococcus aureus, and Myccobacterium tuberculosis, utilizing bending energy calculations. Of the 25 compounds examined, 13 displayed potent activity against all the bacterial strains under study, exhibiting bending energy measurements between -7.4 and -10.7 kcal/mol. The -7.4 kcal/mol value corresponds to the bending energy of the SA12 and SA13 compounds with the 2xct protein (Staphylococcus aureus), whereas the -10.7 kcal/molis linked with the bending energy of SA6 and SA11 compounds with the 6GAV protein (Myccobacterium tuberculosis). Further research will involve a QSAR (Quantitative Structure-Activity Relationship) study aimed at constructing a reliable model to combat the aforementioned bacterial strains and a molecular dynamics study to evaluate the stability of ligand-protein complexes.

Keywords: docking, QSAR, bending energy, e. coli

Procedia PDF Downloads 75

Authors: María Reveles-Miranda, Daniella Pacheco-Catalán

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Sierra Papacal commissary is located north of Merida, Yucatan, México, where the indigenous Maya population predominates. Due to its location, the region has an elevation of fewer than 4.5 meters above sea level, with a high risk of flooding associated with storms and hurricanes and a high vulnerability of infrastructure and housing in the presence of strong gusts of wind. In environmental contingencies, the challenge is providing an autonomous electrical supply using renewable energy sources that cover vulnerable populations' health, food, and water pumping needs. To address this challenge, a hybrid energy storage module is proposed for the emergency photovoltaic (PV) system of the community shelter in Sierra Papacal, Yucatán, which combines high-energy-density batteries and high-power-density supercapacitors (SC) in a single module, providing a quick response to energy demand, reducing the thermal stress on batteries and extending their useful life. Incorporating SC in energy storage modules can provide fast response times to power variations and balanced energy extraction, ensuring a more extended period of electrical supply to vulnerable populations during contingencies. The implemented control strategy increases the module's overall performance by ensuring the optimal use of devices and balanced energy exploitation. The operation of the module with the control algorithm is validated with MATLAB/Simulink® and experimental tests.

Keywords: batteries, community shelter, environmental contingencies, hybrid energy storage, isolated photovoltaic system, supercapacitors

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Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

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There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: chlorodifluoromethane (HCFC-142b), ozone, least squares method, regression models

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Authors: Awni H. Alkhazaleh, Baljinder K. Kandola

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In this study, a form-stable composite Paraffin/Nanoclay (PA-NC) has been prepared by absorbing PA into porous particles of NC to be used for low-temperature latent heat thermal energy storage. The leakage test shows that the maximum mass fraction of PA that can be incorporated in NC without leakage is 60 wt.%. Differential scanning calorimetry (DSC) has been used to measure the thermal properties of the PA and PA-NC both before and after incorporation in plasterboard (PL). The mechanical performance of the samples has been evaluated in flexural mode. The thermal energy storage performance has been studied using a small test chamber (100 mm × 100 mm × 100 mm) made from 10 mm thick PL and measuring the temperatures using thermocouples. The flammability of the PL+PL-NC has been discussed using a cone calorimeter. The results indicate that the form composite PA has good potential for use as thermal energy storage materials in building applications.

Keywords: building materials, flammability, phase change materials, thermal energy storage

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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The sun is an inexhaustible source and harnessing its potential both for heating and for power generation is one of the most promising and necessary alternatives, mainly due to environmental issues. However, it should be noted that this has always been present in the generation of energy on the planet, only indirectly, as it is responsible for virtually all other energy sources, such as: Generates the evaporation source of the water cycle, which allows the impoundment and the consequent generation of electricity (hydroelectricity); Winds are caused by large-scale atmospheric induction caused by solar radiation; Oil, coal and natural gas were generated from waste plants and animals that originally obtained the energy needed for its development of solar radiation. Thus, the idea of using solar energy for practical purposes for the benefit of man is not new, as it accompanies the story since the beginning of time, which means that the sun was always of utmost importance in the design of shelters, or homes is, constructed by taking into consideration the use of sunlight, practicing what was being lost through the centuries, until a time when the buildings started to be designed completely independent of the sun. However, the climatic rigors still needed to be fought, only artificially and today seen as unsustainable, with additional facilities fueled by energy consumption. This paper presents a study on the feasibility of using solar energy for heating water in homes, developing a simplified methodology covering the mode of operation of solar water heaters, solar potential existing alternative systems of Brazil, the international market, and barriers encountered.

Keywords: solar energy, solar heating, solar project, water heating

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Vincent Gauthier, Om Rangacharya, Jordan Lemorande, Senthil Sundaram, James Green, Ghada Alsaleh

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Introduction: Cellular senescence and autophagy are critical processes in aging and age-related diseases. This study examines the effects of Cellular Recharge Technology 8 (CRT8), a proprietary blend of certain supplements on both two-dimensional Human dermal fibroblasts (HDF) and three-dimensional organoid models. Some of the individual ingredients of CRT8 are known to individually have an effect on cellular senescence and autophagy, but their overall effect in the proprietary blend is unknown. The focus of this study is on the impact of CRT8 on cellular senescence and autophagy. Methods: Human dermal fibroblasts (HDF) were treated with CRT8 in 2D cellular studies, assessing effects on p16 (senescence marker) Mean Fluorescence Intensity (MFI), and LC3 (autophagy marker) MFI. The same CRT8 mix was applied to 3D organoid models, composed of HDF and endothelial cells, with results measured after 6 weeks of treatment, focusing on autophagy and senescence markers. Results: In 2D cellular models, CRT8 significantly reduced p16 MFI levels by 40%, indicating a potential decrease in cellular senescence, and increased LC3 MFI by more than 2-fold, demonstrating enhanced autophagic activity. Similarly, in the 3D organoid models, CRT8 significantly reduced p16 MFI levels by 63% and increased autophagic flux by 1.62-fold, further reinforcing its potential to reduce senescence and promote autophagy. Conclusion: CRT8 effectively reduces p16 levels and enhances autophagy in both 2D and 3D models, highlighting its potential as a powerful anti-aging intervention. CRT8 may be valuable in promoting cellular health and longevity.

Keywords: cellular senescence, autophagy, aging, supplements

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Authors: Pratibha Biswal, Suyash Morchhale, Anshuman Singh Yadav, Shubham Sanjay Chobe

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Energy demands are increasing whereas energy sources, especially non-renewable sources are limited. Due to the intermittent nature of renewable energy sources, it has become the need of the hour to find new ways to store energy. Out of various energy storage methods, latent heat thermal storage devices are becoming popular due to their high energy density per unit mass and volume at nearly constant temperature. This work presents a computational fluid dynamics (CFD) model using ANSYS FLUENT 19.0 for energy storage characteristics of a phase change material (PCM) filled in a vertical triplex tube thermal energy storage system. A vertical triplex tube heat exchanger, just like its name consists of three concentric tubes (pipe sections) for parting the device into three fluid domains. The PCM is filled in the middle domain with heat transfer fluids flowing in the outer and innermost domains. To enhance the heat transfer inside the PCM, eight fins have been incorporated between the internal and external tubes. These fins run radially outwards from the outer-wall of innermost tube to the inner-wall of the middle tube dividing the middle domain (between innermost and middle tube) into eight sections. These eight sections are then filled with a PCM. The validation is carried with earlier work and a grid independence test is also presented. Further studies on freezing and melting process were carried out. The results are presented in terms of pictorial representation of isotherms and liquid fraction

Keywords: heat exchanger, thermal energy storage, phase change material, CFD, latent heat

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Authors: Marriette Sakah, Christoph Kuhn, Samuel Gyamfi

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Global electricity demand of households in 2005 is estimated to double by 2025 and nearly double again in 2030. The residential sector promises considerable demand growth through infrastructural and equipment investments, the majority of which is projected to occur in developing countries. This lays bare the urgency for enhanced efficiency in all energy systems combined with exploitation of local potential for renewable energy systems. This study explores options for reducing energy consumption, particularly in residential buildings and providing robust, decentralized and renewable energy supply for African cities. The potential of energy efficiency measures and the potential of harnessing local resources for renewable energy supply are quantitatively assessed. The scale of research specifically addresses the city level, which is regulated by local authorities. Local authorities can actively promote the transition to a renewable-based energy supply system by promoting energy efficiency and the use of alternative renewable fuels in existing buildings, and particularly in planning and development of new settlement areas through the use of incentives, regulations, and demonstration projects. They can also support a more sustainable development by shaping local land use and development patterns in such ways that reduce per capita energy consumption and are benign to the environment. The subject of the current case study, Tema, is Ghana´s main industrial hub, a port city and home to 77,000 families. Residential buildings in Tema consumed 112 GWh of electricity in 2013 or 1.45 MWh per household. If average household electricity demand were to decline at an annual rate of just 2 %, by 2035 Tema would consume only 134 GWh of electricity despite an expected increase in the number of households by 84 %. The work is based on a ground survey of the city’s residential sector. The results show that efficient technologies and decentralized renewable energy systems have great potential for meeting the rapidly growing energy demand of cities in developing countries.

Keywords: energy efficiency, energy saving potential, renewable energy integration, residential buildings, urban Africa

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Authors: M. Sundaram, H. R. Sanath Kumar, A. Ramprakash

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Energy saving is a key sustainability focus area for the Indian telecom industry today. This is especially true in rural India where energy consumption contributes to 70 % of the total network operating cost. In urban areas, the energy cost for network operation ranges between 15-30 %. This expenditure on energy as a result of the lack of grid power availability highlights a potential barrier to telecom industry growth. As a result of this, telecom tower companies switch to diesel generators, making them the second largest consumer of diesel in India, consuming over 2.5 billion litres per annum. The growing cost of energy due to increasing diesel prices and concerns over rising greenhouse emissions have caused these companies to look at other renewable energy options. Even the TRAI (Telecom Regulation Authority of India) has issued a number of guidelines to implement Renewable Energy Technologies (RETs) in the telecom towers as part of its ‘Implementation of Green Technologies in Telecom Sector’ initiative. Our proposal suggests the implementation of a Programmable Logic Controller (PLC) based ‘optimisation controller’ that can not only efficiently utilize the energy from RETs but also help to conserve the power used in the telecom towers. When there are multiple RETs available to supply energy, this controller will pick the optimum amount of energy from each RET based on the availability and feasibility at that point of time, reducing the dependence on diesel generators. For effective maintenance of the towers, we are planing to implement a SCADA based monitoring system along with the ‘optimization controller’.

Keywords: operation costs, consumption of fuel and carbon footprint, implementation of a programmable logic controller (PLC) based ‘optimisation controller’, efficient SCADA based monitoring system

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Authors: Yuzhi Cai

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In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

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Authors: Abdelmalek Ouannou, Adil Brouri, Laila Kadi, Tarik

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Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close.

Keywords: switched reluctance motor, swept-sine signal, generalized Hammerstein model, nonlinear system

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Authors: Lucia Ceccherini Nelli, Alessandra Donato

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The ABITA Master course of the University of Florence offered by the Department of Architecture covers nearly all the energy-relevant issues that can arise in public and private companies and sectors. The main purpose of the Master course, active since 2003, is to analyse the energy consumption of building technologies, components, and structures at the conceptual design stage, so it could be very helpful, for designers, when making decisions related to the selection of the most suitable design alternatives and for the materials choice that will be used in an energy-efficient building. The training course provides a solid basis for increasing the knowledge and skills of energy managers and is developed with an emphasis on practical experiences related to the knowledge through case studies, measurements, and verification of energy-efficient solutions in buildings, in the industry and in the cities. The main objectives are: i)To raise the professional standards of those engaged in energy auditing, ii) To improve the practice of energy auditors by encouraging energy auditing professionals in a continuing education program of professional development, iii) Implement in the use of instrumentations for the typical measurements, iv) To propose an integrated methodology that links energy analysis tools with green building certification systems. This methodology will be applied at the early design stage of a project’s life. The final output of the practical training is to achieve an elevated professionalism in the study of environmental design and Energy management in buildings. The results are the redaction of line guides instruction for the energy refurbishment of Public schools in Florence. The school heritage of the Municipality of Florence requires interventions for the control of energy performance, as old construction buildings are often made without taking into account the necessary envelope performance. For this reason, every year, the Master's course aims to study groups of public schools to enable the Municipality to carry out energy redevelopment interventions on the existing building heritage. The future challenges of the education and training program are related to follow-up activities, the development of interactive tools and the curriculum's customization to meet the constantly growing needs of energy experts from industry.

Keywords: expert in energy, energy auditing, public buildings, thermal analysis

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Authors: Mohamed Moustafa Mahmoud Sedky

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The double-fed induction generator wind turbine has recently received a great attention. The steady state performance and response of double fed induction generator (DFIG) based wind turbine are now well understood. This paper presents the analysis of stator and rotor flux linkage dq models operation of DFIG under different faults and at different locations.

Keywords: double fed induction motor, wind energy, flux linkage, short circuit

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Authors: I. O. Nascimento, J. T. Manzi

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The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.

Keywords: thermodynamic optimization, drying, entropy minimization, modeling dryers

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Authors: Aqsa Asharaf

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The current study aims to examine the physical characteristics of charge compact spheres employing anisotropic fluid under f(R, ϕ, X) modified gravity approach, exploring how this theoretical context influences their attributes and behavior. To accomplish our goal, we adopt the Spherically Symmetric (SS) space-time and, additionally, employ a specific Adler-based mode for the metric potential (gtt), which yields a broader class of solutions, Then, by making use of the Karmarkar condition, we successfully derive the other metric potential. A primary component of our current analysis is utilizing the Bardeen geometry as extrinsic space-time to determine the constant parameters of intrinsic space-time. Further, to validate the existence of Bardeen stellar spheres, we debate the behavior of physical properties and parameters such as components of pressure, energy density, anisotropy, parameters of EoS, stability and dynamical equilibrium, energy bounds, mass function, adiabatic index, compactness factor, and surface redshift. Conclusively, all the obtained results show that the system under consideration is physically stable, free from singularity, and viable models.

Keywords: cosmology, GR, Bardeen BH, modified gravities

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Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Janaina Camile Pasqual Lofhagen, David Savarese, Veronika Vazhnik

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The urgency of the climate crisis requires both innovation and practicality. The energy transition framework allows industry to deliver resilient cities, enhance adaptability to change, pursue energy objectives such as growth or efficiencies, and increase renewable energy. This paper investigates a real-world application perspective for the use of biogas in Brazil and the U.S.. It will examine interventions to provide a foundation of infrastructure, as well as the tangible benefits for policy-makers crafting law and providing incentives.

Keywords: resilience, vulnerability, risks, biogas, sustainability.

Procedia PDF Downloads 96

Authors: Saeed Vahidifar, Mohammad Nakhaee Sharif, Mohammad Ghaffari

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Few people would dispute the fact that one of the most common applications of energy is creating comfort in buildings, so it is probably true to say that management of energy consumption is required due to the environmental issues and increasing the efficiency of mechanical systems. From the geographical point of view, Iran is located in a warm and semi-arid region; therefore, air-cooled chillers are usually used for cooling residential buildings, commercial buildings, medical buildings, etc. In this study, a heat exchanger was designed for providing laundry hot water by utilizing condenser heat lost base on analytical results of a 540-bed hospital in the city of Mashhad in Iran. In this paper, by using the analytical method, energy consumption reduces about 13%, and coefficient of performance increases a bit. Results show that this method can help in the management of energy consumption a lot.

Keywords: air cooled chiller, energy management, environmental issues, heat exchanger, hospital laundry system

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Authors: Rajneekant Bachan, Dhanush Vijay

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The visualization of operating systems has refined the Turing machine, and current trends suggest that the emulation of 32 bit architectures will soon emerge. After years of technical research into Web services, we demonstrate the synthesis of gigabit switches, which embodies the robust principles of theory. Loam, our new algorithm for forward-error correction, is the solution to all of these challenges.

Keywords: software engineering, architectures, introspective models, operating systems

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Authors: Wu Xingchun, Chen Xi

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Nowadays, China's building energy consumption constitutes 25% of the total energy consumption, half of which was caused by air conditioning in both summer and winter. The ventilation system in Chinese traditional residence, which is totally passive and environmentally friendly, works effectively to create comfortable indoor environment. The research on the ventilation system in Chinese traditional residence can provide advancements to architecture design and energy savings to the society. Through field investigation, case analysis, strategy proposing and other methods, it comes out that the location and layout, the structure system and the design of atrium are the most important elements for a good ventilation system. Taking every factor into consideration, techniques are deployed extensively such as the organization of draught, the design of the thermal pressure ventilation system and the application of modern materials. With the enlightenment of the ventilation system in Chinese traditional residence, we can take effective measures to achieve low energy consumption and sustainable architecture.

Keywords: ventilation system, chinese traditional residence, energy consumption, sustainable architecture

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Authors: Asser S. Abdelwahab, Nabil H. Abbasy, Ragi A. Hamdy

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Marine shipping has now become one of the major worldwide contributors to pollution and greenhouse gas emissions. Hybrid ships technology based on multiple energy sources has taken a great scope of research to get rid of ship emissions and cut down fuel expenses. Insufficiency between power generated and the demand load to withstand the transient behavior on ships during severe climate conditions will lead to a blackout. Thus, an efficient energy management system (EMS) is a mandatory scope for achieving higher system efficiency while enhancing the lifetime of the onboard storage systems is another salient EMS scope. Considering energy storage system conditions, both the battery state of charge (SOC) and temperature represent important parameters to prevent any malfunction of the storage system that eventually degrades the whole system. In this paper, a two battery packs ratio fuzzy logic control model is proposed. The overall aim is to control the charging/discharging current while including both the battery SOC and temperature in the energy management system. The full designs of the proposed controllers are described and simulated using Matlab. The results prove the successfulness of the proposed controller in stabilizing the system voltage during both loading and unloading while keeping the energy storage system in a healthy condition.

Keywords: energy storage system, power shipboard, hybrid ship, thermal runaway

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Authors: Hoda Aslani, Mohammad Moghiman, Mohammad Aslani

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Considering the demand to reduce global warming potential and importance of solidification in various applications, there is an increasing interest in energy storage systems to find the efficient phase change materials. Therefore, this paper presents an experimental study and comparison on the potential of titania nanofluids with and without surfactant for cooling energy storage systems. A designed cooling generation device based on compression refrigeration cycle is used to explore nanofluids solidification characteristics. In this work, titania nanoparticles of 0.01, 0.02 and 0.04 wt.% are dispersed in deionized water as base fluid. Measurement of phase change parameters of nanofluids illustrates that the addition of polyvinylpyrrolidone (PVP) as surfactant to titania nanofluids advances the onset nucleation time and leads to lower solidification time. Also, the experimental results show that only adding 0.02 wt.% titania nanoparticles, especially in the case of nanofluids with a surfactant, can evidently reduce the supercooling degree by nearly 70%. Hence, it is concluded that there is a great energy saving potential in the energy storage systems using titania nanofluid with PVP.

Keywords: cooling energy storage, nanofluid, PVP, solidification, titania

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Rohit Shrivastava, Stefan Luding

Abstract:

A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

Abstract:

Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

Procedia PDF Downloads 83