Search results for: low energy consumption

Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Helena López-Moreno, Antoni Rodríguez-Sánchez, Carmen Viñas-Arrebola, Cesar Porras-Amores

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The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 100% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades does not improve the thermal lag significantly (p > 0.05) when compared to the SLVF façade.

Keywords: ventilated façade, energy efficiency, thermal behavior, statistical analysis

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Authors: Abul Quasem Al-Amin, Md. Hasanuzzaman, Mohammad Nurul Azam, Walter Leal Filho

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With regard to the future energy strategy and vision, this study aimed to find the drawbacks of proposed energy diversification policy for 2020. To have a clear picture of the drawback and competitive alternative, this study has explored two scenarios, namely Scenario a and Scenario b. The Scenario a indicates that in the year 2020 the GHG emissions would be 823,498.00 million tons (Mt) with a 2020 final demand and proposed fuel mix such as by the Five-Fuel Diversification Strategy. In contrast, as an alternative, the Scenario b with biofuel potentials indicates that the substitution of coal energy by 5%, 10%, and 15%, respectively, with biofuel, would reduce the GHG emissions from 374,551.00, 405,118.00, and 823,498.00 million tons to 339,964.00, 329,834.00, and 305,288.00 million tons, respectively, by the present fuel mix, business-as-usual fuel mix, and proposed fuel mix up to the year 2020. Therefore, this study has explored a healthy alternative by introducing biofuel renewable energy option instead of conventional energy utilization in the power generation with environmental aspect in minds. This study effort would lessen the gap between GHG mitigation and future sustainable development and would useful to formulate effective renewable energy strategy in Malaysia.

Keywords: energy, environmental impacts, renewable energy, biofuel, energy policy

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Authors: W. Benstaali, A. Belasri

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In this work we study a planar lamp filled with neon-xenon gas. We use a one-dimensional particle in a cell with Monte Carlo simulation (PIC-MCC) to investigate the effect xenon concentration on the energy deposited on excitation, ionization and ions. A Xe-Ne discharge is studied for a gas pressure of 400 torr. The results show an efficient Xe20-Ne mixture with an applied voltage of 1.2KV; the xenon excitation energy represents 65% form total energy dissipated in the discharge. We have also studied electrical properties and the energy balance a discharge for Xe50-Ne which needs a voltage of 2kv; the xenon energy is than more important.

Keywords: dielectric barrier discharge, efficiency, excitation, lamps

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Authors: Guarry Montrose, Ted Soubdhan

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In the context of sustainable development and climate change, the adaptation of buildings to the climatic context in hot climates is a necessity if we want to improve living conditions in housing and reduce the risks to the health and productivity of occupants due to thermal discomfort in buildings. One can find a wide variety of efficient solutions but with high costs. In developing countries, especially tropical countries, we need to appreciate a technology with a very limited cost that is affordable for everyone, energy efficient and protects the environment. Biosourced insulation is a product based on plant fibers, animal products or products from recyclable paper or clothing. Their development meets the objectives of maintaining biodiversity, reducing waste and protecting the environment. In tropical or hot countries, the aim is to protect the building from solar thermal radiation, a source of discomfort. The aim of this work is in line with the logic of energy control and environmental protection, the approach is to make the occupants of buildings comfortable, reduce their carbon dioxide emissions (CO₂) and decrease their energy consumption (energy efficiency). We have chosen to study the thermo-physical properties of banana leaves and sawdust, especially their thermal conductivities, direct measurements were made using the flash method and the hot plate method. We also measured the heat flow on both sides of each sample by the hot box method. The results from these different experiences show that these materials are very efficient used as insulation. We have also conducted a building thermal simulation using banana leaves as one of the materials under Design Builder software. Air-conditioning load as well as CO₂ release was used as performance indicator. When the air-conditioned building cell is protected on the roof by banana leaves and integrated into the walls with solar protection of the glazing, it saves up to 64.3% of energy and avoids 57% of CO₂ emissions.

Keywords: plant fibers, tropical climates, sustainable development, waste reduction

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Authors: G. N. Tiwari, Shyam

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Photovoltaic thermal (PVT) roof type greenhouse dryer installed above the wind tower of SODHA BERS COMPLEX, Varanasi has been analyzed for all types of weather conditions. The product to be dried has been kept at three different trays. The upper tray receives energy from the PV cover while the bottom tray receives thermal energy from the hot air of the wind tower. The annual energy estimation has been done for the all types of weather condition of composite climate of northern India. It has been found that maximum energy saving is observed for c type of weather condition whereas minimum energy saving is observed for a type of weather condition. The energy saving on overall thermal energy basis and exergy basis are 1206.8 kWh and 360 kWh respectively for c type of weather condition. The energy saving from all types of weather condition are found to be 3175.3 kWh and 957.6 kWh on overall thermal energy and overall exergy basis respectively.

Keywords: exergy, greenhouse, photovoltaic thermal, solar dryer

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Authors: Willian C. De Brito, Hernan D. C. Munoz, Erlan V. C. Carvalho, Helder L. C. De Oliveira

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In order to improve commute time for small distance trips and relieve large cities traffic, a new transport category has been the subject of research and new designs worldwide. The air taxi travel market promises to change the way people live and commute by using the concept of vehicles with the ability to take-off and land vertically and to provide passenger’s transport equivalent to a car, with mobility within large cities and between cities. Today’s civil air transport remains costly and accounts for 2% of the man-made CO₂ emissions. Taking advantage of this scenario, many companies have developed their own Vertical Take Off and Landing (VTOL) design, seeking to meet comfort, safety, low cost and flight time requirements in a sustainable way. Thus, the use of green power supplies, especially batteries, and fully electric power plants is the most common choice for these arising aircrafts. However, it is still a challenge finding a feasible way to handle with the use of batteries rather than conventional petroleum-based fuels. The batteries are heavy and have an energy density still below from those of gasoline, diesel or kerosene. Therefore, despite all the clear advantages, all electric aircrafts (AEA) still have low flight autonomy and high operational cost, since the batteries must be recharged or replaced. In this sense, this paper addresses a way to optimize the energy consumption in a typical mission of an aerial taxi aircraft. The approach and landing procedure was chosen to be the subject of an optimization genetic algorithm, while final programming can be adapted for take-off and flight level changes as well. A real tilt rotor aircraft with fully electric power plant data was used to fit the derived dynamic equations of motion. Although a tilt rotor design is used as a proof of concept, it is possible to change the optimization to be applied for other design concepts, even those with independent motors for hover and cruise flight phases. For a given trajectory, the best set of control variables are calculated to provide the time history response for aircraft´s attitude, rotors RPM and thrust direction (or vertical and horizontal thrust, for independent motors designs) that, if followed, results in the minimum electric power consumption through that landing path. Safety, comfort and design constraints are assumed to give representativeness to the solution. Results are highly dependent on these constraints. For the tested cases, performance improvement ranged from 5 to 10% changing initial airspeed, altitude, flight path angle, and attitude.

Keywords: air taxi travel, all electric aircraft, batteries, energy consumption, genetic algorithm, landing performance, optimization, performance improvement, tilt rotor, VTOL design

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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In this paper, a non-cooperative game method is formulated where all players compete to transmit at higher power. Every base station represents a player in the game. The game is solved by obtaining the Nash equilibrium (NE) where the game converges to optimality. The proposed method, named Power Efficient Handover Game Theoretic (PEHO-GT) approach, aims to control the handover in dense small cell networks. Players optimize their payoff by adjusting the transmission power to improve the performance in terms of throughput, handover, power consumption and load balancing. To select the desired transmission power for a player, the payoff function considers the gain of increasing the transmission power. Then, the cell selection takes place by deploying Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A game theoretical method is implemented for heterogeneous networks to validate the improvement obtained. Results reveal that the proposed method gives a throughput improvement while reducing the power consumption and minimizing the frequent handover.

Keywords: energy efficiency, game theory, handover, HetNets, small cells

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Authors: Chunduru Amareswara Prasad

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The main aim of this proposal it to reveal the secrets of the universe by accelerating neutrons. The proposal idea in its abridged version speaks about the possibility of making neutrons accelerate with help of thermal energy and magnetic energy under controlled conditions. Which is helpful in revealing the hidden secrets of the universe namely dark energy and in finding properties of Higgs boson. The paper mainly speaks about accelerating neutrons to near velocity of light in a LINAC, using magnetic energy by magnetic pressurizers. The center of mass energy of two colliding neutron beams is 94 GeV (~0.5c) can be achieved using this method. The conventional ways to accelerate neutrons has some constraints in accelerating them electromagnetically as they need to be separated from the Tritium or Deuterium nuclei. This magnetic gradient method provides efficient and simple way to accelerate neutrons.

Keywords: neutron, acceleration, thermal energy, magnetic energy, Higgs boson

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Authors: B. A. Adeniyi, S. A. Daud, O. Amao

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The study investigates consumer demand for meat products in Oyo West Local Government using linear approximate almost ideal demand system (LA/AIDS). Questions that were addressed by the study include: first, what is the type and quantity of meat products available to the household and their demand pattern? Second is the investigation of the factors that affect meat products demand pattern and proportion of income that is spent on them. For the above purpose cross-sectional data were collected from 156 households of the study area and analyzed to reveal the functional relationship between meat products consumption and some socio-economic variables of the household. Results indicated that per capita meat consumption increased as household income and education increased but decreased with age. It was also found that male tend to consume more meat products than their female counterparts and that increase in household size will first increased per caput meat consumption but later decreased it. Price also tends to greatly influence the demand pattern of meat products. The results of elasticity computed from the results of regression analysis revealed that own price elasticity for all meat products were negative which indicated that they were normal products while cross and expenditure elasticity were positive which further confirmed that meat products were normal and substitute products. This study therefore concludes that the relevance of these variables imposed a great challenge to the policy makers and the government, in the sense that more cost effective methods of meat production technology have to be devised in other to make consumption of meat products more affordable.

Keywords: meat products, consumption, animal production, technology

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Authors: Parvin Mirmiran, Zahra Bahadoran, Nazanin Moslehi, Fereidoun Azizi

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Background and aim: We aimed to investigate the effects of green fruits and vegetables (green FV) consumption on the 3-year changes of cardiometabolic risk factors. Methods: This longitudinal study was conducted in the framework of Tehran Lipid and Glucose Study, between 2006-2008 and 2009-2011, on 1272 adults. Dietary intake of green FV, including green cabbage, broccoli, lettuce, celery, green beans, green peas, cucumber, leafy vegetables, zucchini, green chili and bell pepper, and kiwi fruit, has been assessed by a validated semi-quantitative food frequency questionnaire at baseline and second examination. Demographics, anthropometrics and biochemical measures were evaluated at baseline and 3 years later. The associations of cardiometabolic risk changes with mean intake of green FV were estimated. Results: The mean age of men and women at baseline was 39.8±12.7 and 37.3±12.1 years, respectively. Mean intake of green FV was 152±77 g/d. More intake from green FV was accompanied to more intake of vitamin A, α and β-carotene, lutein, β-criptoxanthine, potassium, magnesium and fiber. Consumption of green FV was inversely associated with 3-year change of waist circumference (β= -0.07, P=0.01), total cholesterol (β= -0.11, P=0.01) and triglycerides (β= -0.13, P=0.01). Each 25 g/d increase in consumption of green FV decreased the incidence of hyper-triglyceridemia by 12% (OR:0.88, 95%CI:0.71-0.99) in men. In women, no significant association was observed between consumption of green FV with cardiometabolic risk factors. Conclusion: Higher consumption of green FV could have preventive effects against abdominal fat gain and lipid disorders.

Keywords: cardiometabolic risk factors, abdominal obesity, lipid disorders, fruits, vegetables

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Jae Hee Chung, Tae Uk Kang, Byung Seo Kim

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This study aims to propose design technologies for the energy-saving modular housing units considering environmental and aesthetic aspects. Modular houses are environmentally friendly based on 3R (Reduce, Reuse, Recycle) because they can dramatically reduce carbon dioxide and construction wastes generated during the construction, use, and disposal process by the pre-fabrication at the factory and the recyclability of the unit, compared to the existing construction methods. The existing modular housing, however, tends to focus on quantitative aspects of energy reduction, such as windows, insulation, and introduction of renewable energy, and there is not much research on energy-saving type units considering the environmental aspects such as daylighting and ventilation, and the design that goes beyond the standardized appearance. Therefore, this study conducts theoretical investigation and analytical case studies on the energy-saving methods through various architectural planning elements as well as materials like insulation considering the environmental and aesthetic aspects in the modular housing. Then, comparative analysis on the energy efficiency through the energy simulation is conducted. As a conclusion, the energy-saving modular housing units considering environmental and aesthetics aspects are proposed. It is expected that this study will contribute to the supply and activation of modular housing through deriving design technologies for the energy-saving modular housing units that consider not only quantitative aspects but also qualitative aspects.

Keywords: aesthetic aspects, energy-saving, environmental, modular housing

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Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

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Authors: Khaled M. Khader, Mamdouh I. Elimy, Omayma A. Nada

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Sustainable development is the nominal goal of most countries at present. In general, fossil fuels are the development mainstay of most world countries. Regrettably, the fossil fuel consumption rate is very high, and the world is facing the problem of conventional fuels depletion soon. In addition, there are many problems of environmental pollution resulting from the emission of harmful gases and vapors during fuel burning. Thus, clean, renewable energy became the main concern of most countries for filling the gap between available energy resources and their growing needs. There are many renewable energy sources such as wind, solar and wave energy. Energy can be obtained from the motion of sea waves almost all the time. However, power generation from solar or wind energy is highly restricted to sunny periods or the availability of suitable wind speeds. Moreover, energy produced from sea wave motion is one of the cheapest types of clean energy. In addition, renewable energy usage of sea waves guarantees safe environmental conditions. Cheap electricity can be generated from wave energy using different systems such as oscillating bodies' system, pendulum gate system, ocean wave dragon system and oscillating water column device. In this paper, a multi-criteria model has been developed using Analytic Hierarchy Process (AHP) to support the decision of selecting the most effective system for generating power from sea waves. This paper provides a widespread overview of the different design alternatives for sea wave energy converter systems. The considered design alternatives have been evaluated using the developed AHP model. The multi-criteria assessment reveals that the off-shore Oscillating Water Column (OWC) system is the most appropriate system for generating power from sea waves. The OWC system consists of a suitable hollow chamber at the shore which is completely closed except at its base which has an open area for gathering moving sea waves. Sea wave's motion pushes the air up and down passing through a suitable well turbine for generating power. Improving the power generation capability of the OWC system is one of the main objectives of this research. After investigating the effect of some design modifications, it has been concluded that selecting the appropriate settings of some effective design parameters such as the number of layers of Wells turbine fans and the intermediate distance between the fans can result in significant improvements. Moreover, simple dynamic analysis of the Wells turbine is introduced. Furthermore, this paper strives for comparing the theoretical and experimental results of the built experimental prototype.

Keywords: renewable energy, oscillating water column, multi-criteria selection, Wells turbine

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Authors: Shigeyuki Haruyama, Oke Oktavianty, Zefry Darmawan, Tadayuki Kyoutani, Ken Kaminishi

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Cab’s frame strength is considered as an important factor in excavator’s operator safety, especially during roll-over. In this study, we use a model of cab frame with different thicknesses and perform elastoplastic numerical analysis by using Finite Element Method (FEM). Deformation mode and energy absorption's of cab’s frame part are investigated on two conditions, with wrinkle and without wrinkle. The occurrence of wrinkle when deforming cab frame can reduce energy absorption, and among 4 parts with wrinkle, the energy absorption significantly decreases in part C. Residual stress that generated upon the bending process of part C is analyzed to confirm it possibility in increasing the energy absorption.

Keywords: ROPS, FEM, hydraulic excavator, cab frame

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Authors: Ahmad Rouhani

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Iran has several potentials for using renewable energies, so use them could significantly contribute to energy supply. The purpose of this paper is to identify the potential of the country and select the appropriate DG technologies with consideration the potential and primary energy resources in the regions. In this context, hybrid energy systems proportionate with the potential of different regions will be determined based on technical, economic, and environmental aspect. In the following, the proposed structure will be optimized in terms of size and cost. DG technologies used in this project include the photovoltaic system, wind turbine, diesel generator, and battery bank. The HOMER software is applied for choosing the appropriate structure and the optimization of system sizing. The results have been analyzed in terms of technical and economic. The performance and the cost of each project demonstrate the appropriate structure of hybrid energy system in that region.

Keywords: feasibility, hybrid energy system, Iran, renewable energy

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Authors: Gatoto Placide, Michel Roddy Lollchund, Gace Athanase Dalson

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This paper first presents a review of the current situation of energy access rate in Burundi, which is relatively low compared to other countries. The paper aims to identify the key gaps in improving the electrical energy access in Burundi and proposes a solution to overcome these gaps. It is shown that the electrical power grid is old and concentrated in north-west and in Bujumbura city while other regions lack access to national grids. Next to that, the link between electricity access and sustainable development in Burundi is clarified. Further, some solutions are suggested to solve energy access problems such as the electricity transmission lines extension and renovation, diversification of energy sources.

Keywords: Burundi, energy access, hydropower, sustainable development

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Authors: Hamid Rostami, Ali Fallah Yeznabad, Mohammad H. Baziar

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The energy-based method for evaluating seismic soil liquefaction has two main sections. First is the demand energy, which is dissipated energy of earthquake at a site, and second is the capacity energy as a representation of soil resistance against liquefaction hazard. In this study, using a statistical analysis of recorded data by 14 down-hole array sites in California, an empirical equation was developed to estimate the demand energy at sites. Because determination of capacity energy at a site needs to calculate several site calibration factors, which are obtained by experimental tests, in this study the standard penetration test (SPT) N-value was assumed as an alternative to the capacity energy at a site. Based on this assumption, the empirical equation was employed to calculate the demand energy for 193 liquefied and no-liquefied sites and then these amounts were plotted versus the corresponding SPT numbers for all sites. Subsequently, a discrimination analysis was employed to determine the equations of several boundary curves for various liquefaction likelihoods. Finally, a comparison was made between the probabilistic model and the commonly used stress method. As a conclusion, the results clearly showed that energy-based method can be more reliable than conventional stress-based method in evaluation of liquefaction occurrence.

Keywords: energy demand, liquefaction, probabilistic analysis, SPT number

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Authors: Beril Tuğrul

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Electrical energy is the most important form of energy and electrical power plants have highest impact factor in energy policy. This study is in relation with evaluation of various power plants including fossil fuels, nuclear and renewable energy based power plants. The power plants evaluated with regard to their overall impact that considered for establishing of the plants. Both positive and negative impacts of power plant operation are compared view of different arguments. Then calculate the impact factor by using variation linear extrapolation for each argument. With this study, power plants assessed with the different point of view and clarified objectively.

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Procedia PDF Downloads 524

Authors: Nimot Opeyemi Wahab

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Poor nutritional status during adolescence is a reflection of inadequate intake of nutrients. This can also be associated with a lack of consumption of diverse food. This study assessed the nutritional status and dietary diversity score (DDS) of in-school adolescents in Ibadan North, North East, and Ibadan South West Local Government Areas (LGA) of Oyo State, Nigeria. A cross-sectional study involving 3,510 in-school adolescents from the three LGA was conducted. Nutrient intake was measured using a validated 24-hour dietary recall, and the anthropometric measurement was also taken. Dietary diversity score (DDS) was assessed using the Individual Dietary Diversity Score (WDDS) of nine food groups. Participants were between 10-19years, and the mean age was 14.76±1.68, 15.32±1.77, and 15.45±1.62 in Ibadan North, Ibadan North East, and Ibadan South West, respectively. About 48% of the participants were male (47.9%), while 52.1% were female. BMI-for-age showed that 92.1%, 5.4%, 2.1%, and 0.4% of the participants were normal, underweight, overweight, and obese, respectively. The mean energy intake (143.193±695.98) of the female respondents was more than that of the male respondents (1406.86±767.41). The macronutrients intake (protein, carbohydrates, fiber, and fats) of the female participants was also found to be more than that of the male participants, with a non-significant difference of 0.336, 0.530, 0.234, and 0.069 (at p< 0.05). Out of all the vitamin intake, only vitamin C was found to be statistically different (p=0.038) at p<0.05 between the male and female respondents. Of all the mineral intake, only phosphorus showed a higher intake (575.20±362.12) among female respondents than the male respondents. The mean DDS of all participants was 4.59±0.939. The majority of the participants, 1183 (80.9%), were within the medium DDS category, 9.9% were low, while 1.5% were in the high category: of which males were 474 (71.5%) and females were 709 (88.6%). Participants from Ibadan North were 941(88.5%), and those from South West were 242(60.5%). A non-significant difference in the mean score of participants from the two locations (p=0.467) was also found. A negative correlation exists between DDS and BMI-for age (-0.11), DDS, and energy intake (-0.46) in Ibadan North and South West LGA. The nutritional status of in-school adolescents was normal, and DDS was within the medium category. Nutrition intervention regarding the consumption of diverse food is necessary among adolescents.

Keywords: nutritional status, dietary diversity, adolescents, nutrient intake

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Authors: Iara Rezende, Djalma Silva, Alcino Costa Neto

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Considering the transformations of the contemporary world linked to globalization and climate changes caused by global warming, the environmental and energy issues have been increasingly present in the decisions of the world scenario. Thus, the aim of reducing the impacts caused by human activities there are the energy efficiency measures, which are also applicable in the scope of Civil Engineering. Considering that a large part of the energy demand from buildings is related to the need to adapt the internal environment to the users comfort and productivity, measures capable of reducing this need can minimize the climate changes impacts and also the energy consumption of the building. However, these important measures are currently little used by civil engineers, either because of the interdisciplinarity of the subject, the time required to apply certain methods or the difficult interpretation of the results obtained by computational programs that often have a complex and little applied approach. Thus, it was proposed the development of a Java application with a simpler and applied approach to evaluate the thermal performance of a building in order to obtain results capable of assisting the civil engineers in the decision making related to the users thermal comfort. The program was built in Java programming language and the method used for the evaluation was the Center Scientifique et Technique du Batiment (CSTB) method. The program was used to evaluate the thermal performance of a university classroom. The analysis was carried out from simulations considering the worst climatic situation of the building occupation. Thus, at the end of the process, the favorable result was obtained regarding the classroom comfort zone and the feasibility of using the program, thus achieving the proposed objectives.

Keywords: building occupation, CSTB method, energy efficiency measures, Java application, thermal comfort

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Authors: H. Zormati, J. Chebil, J. Bel Hadj Taher

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The goal of this paper is to present an addressing scheme that allows for assigning a unique IPv6 address to each node in the Internet of Things (IoT) network. This scheme guarantees uniqueness by extracting the clock skew of each communication device and converting it into an IPv6 address. Simulation analysis confirms that the presented scheme provides reductions in terms of energy consumption, communication overhead and response time as compared to four studied addressing schemes Strong DAD, LEADS, SIPA and CLOSA.

Keywords: addressing, IoT, IPv6, network, nodes

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Francois Brambati, Daniele Ruscio, Federica Biassoni, Rebecca Hueting, Alessandra Tedeschi

Abstract:

This research, in the frame of social acceptance of renewable energies and community-based production and consumption models, aims at (1) supporting a data-driven approachable to dealing with climate change and (2) identifying & quantifying the psycho-sociological dimensions and factors that could support the transition from a technology-driven approach to a consumer-driven approach throughout the emerging “prosumer business models.” In addition to the existing Social Acceptance dimensions, this research tries to identify a purely individual psychological fourth dimension to understand processes and factors underling individual acceptance and adoption of renewable energy business models, realizing a Prosumer Acceptance Index. Questionnaire data collection has been performed throughout an online survey platform, combining standardized and ad-hoc questions adapted for the research purposes. To identify the main factors (individual/social) influencing the relation with renewable energy technology (RET) adoption, a Factorial Analysis has been conducted to identify the latent variables that are related to each other, revealing 5 latent psychological factors: Factor 1. Concern about environmental issues: global environmental issues awareness, strong beliefs and pro-environmental attitudes rising concern on environmental issues. Factor 2. Interest in energy sharing: attentiveness to solutions for local community’s collective consumption, to reduce individual environmental impact, sustainably improve the local community, and sell extra energy to the general electricity grid. Factor 3. Concern on climate change: environmental issues consequences on climate change awareness, especially on a global scale level, developing pro-environmental attitudes on global climate change course and sensitivity about behaviours aimed at mitigating such human impact. Factor 4. Social influence: social support seeking from peers. With RET, advice from significant others is looked for internalizing common perceived social norms of the national/geographical region. Factor 5. Impact on bill cost: inclination to adopt a RET when economic incentives from the behaviour perception affect the decision-making process could result in less expensive or unvaried bills. Linear regression has been conducted to identify and quantify the factors that could better predict behavioural intention to become a prosumer. An overall scale measuring “acceptance of a renewable energy solution” was used as the dependent variable, allowing us to quantify the five factors that contribute to measuring: awareness of environmental issues and climate change; environmental attitudes; social influence; and environmental risk perception. Three variables can significantly measure and predict the scores of the “Acceptance in becoming a prosumer” ad hoc scale. Variable 1. Attitude: the agreement to specific environmental issues and global climate change issues of concerns and evaluations towards a behavioural intention. Variable 2. Economic incentive: the perceived behavioural control and its related environmental risk perception, in terms of perceived short-term benefits and long-term costs, both part of the decision-making process as expected outcomes of the behaviour itself. Variable 3. Age: despite fewer economic possibilities, younger adults seem to be more sensitive to environmental dimensions and issues as opposed to older adults. This research can facilitate policymakers and relevant stakeholders to better understand which relevant psycho-sociological factors are intervening in these processes and what and how specifically target when proposing change towards sustainable energy production and consumption.

Keywords: behavioural intention, environmental risk perception, prosumer, renewable energy technology, social acceptance

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

Abstract:

In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Arijit Chakraborty, Anirban Roy

Abstract:

The Indian peninsula is strategically located in the Asian subcontinent with the Himalayas to the North and Oceans surrounding the other three directions with annual monsoons which takes care of water supply to the rivers. The total river water discharge into the Bay of Bengal and the Arabian Sea is 628 km³/year and 274 km³/year, respectively. Thus huge volumes of fresh water meet saline water, and this mixing of two streams of dissimilar salinity gives rise to tremendous mixing energies which can be harvested for various purposes like energy generation using pressure retarded osmosis or reverse electrodialysis. The present paper concentrates on analyzing the energy of mixing for the rivers in Goa. Goa has 10 rivers of various sizes all which meet the Arabian Sea. In the present work, the 8 rivers and their salinity (NaCl concentrations) have been analyzed along with their seasonal fluctuations. Next, a Gibbs free energy formulation has been implemented to analyze the energy of mixing of the selected rivers. The highest and lowest energies according to the seasonal fluctuations have been evaluated, and this provides two important insights into (i) amount of energy that can be harvested and (ii) decision on the location of such systems.

Keywords: Gibbs energy, mixing energy, salinity gradient energy, thermodynamics

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Authors: T. Tahri, H. Zahloul, K. E. Meddah, H. Lazergue

Abstract:

This paper presents a theoretical study that leads to the design of a photovoltaic pumping system to irrigate six hectares of oranges in the valley of Chlef using the software "PVSYST". It was shown that the site of Chlef presents a favorable climate to this type of energy with an irradiation of over 5 kWh/m2/day, and significant resources underground water. Another very important coincidence still promotes the use of this type of energy for pumping water in Chlef is that the demand for water, especially in agriculture, peaked in hot and dry where it is precisely when one has access to the maximum of solar energy.

Keywords: solar energy, irradiation, water pumping, design, Valley of Chlef

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Authors: Jianghua Chen

Abstract:

Sustainable urban development requires the coordination of economic growth and resource environment, and industrial transformation and upgrading is the key link. Based on the decoupling theory and the improved decoupling decomposition model, the quantitative evaluation and comprehensive analysis of the degree of decoupling between resource consumption and economic development in Jiangsu Province are conducted using the data related to the resource consumption and economic growth of the secondary and tertiary industries in Jiangsu Province from 2013 to 2018, as a way of exploring the sustainable development path of industrial transformation in Jiangsu Province. The results show that from the decoupling status, the degree of decoupling of economic development of the secondary industry to the required coke resources, water resources, and human resources is gradually deepening, and the decoupling index of economic development of the tertiary industry to the required water resources is fluctuating; from the perspective of the driving factors, the technological effect is the main driving factor to decouple the economic growth of Jiangsu Province to the resources, and the structural effect has a significant impact on the driving index of the decoupling of economic growth of the secondary and tertiary industries to the consumption of resources in Jiangsu Province. Finally, we discuss the difficulties of industrial transformation and layout faced by Jiangsu Province at present.

Keywords: resource consumption, economic growth, industrial transformation, decoupling theory

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Authors: Saleh Komies, Mona Alharbi, Razan Alhayyani, Mozah Almulhim, Roseanne Khawaja, Ahmed Alradhi

Abstract:

One of the proposed solutions that faces some challenges is encouraging sustainable energy consumption across Saudi Arabia through crowdfunding platforms. To address these challenges, we need to determine the level of awareness of crowdfunding and green projects, as well as the preferences and willingness of Saudis to utilize crowdfunding as an alternative funding source for green projects in Saudi Arabia. In this study, we aim to determine the influence of environmental awareness and concern on the propensity to crowdfund green projects. The survey is being conducted as part of environmental initiatives to assess public perceptions and opinions on crowdfunding green projects in Saudi Arabia. A total of 450 responses to an online questionnaire distributed via convenience and snowball sampling were utilized for data analysis. The survey reveals that Saudis have a low understanding of crowdfunding concepts and a relatively high understanding of implementing green projects. The public is interested in crowdfunding green projects if there is a return on investment.

Keywords: crowdfunding, green projects, awareness, Saudi Arabia, energy, solar, wind

Procedia PDF Downloads 99