Search results for: building energy prediction

Authors: Farha Ibrahim, Ely Zarina Samsudin, Ahmad Razali Ishak, Jeyanthini Sathasivam

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Introduction: Indoor air quality (IAQ) has recently gained substantial traction as the airborne transmission of infectious respiratory disease has become an increasing public health concern. Public hospital outpatient department (OPD). IAQ warrants special consideration as it is the most visited department in which patients and staff are all directly impacted by poor IAQ. However, there is limited evidence on IAQ in these settings. Moreover, occupants’ behavior like occupant’s movement and operation of door, windows and appliances, have been shown to significantly affect IAQ, yet the influence of these determinants on IAQ in such settings have not been established. Objectives: This study aims to examine IAQ in Malaysian public hospitals OPD and assess its relationships with occupants’ behavior. Methodology: A multicenter cross-sectional study in which stratified random sampling of Johor public hospitals OPD (n=6) according to building age was conducted. IAQ measurements include indoor air temperature, relative humidity (RH), air velocity (AV), carbon dioxide (CO2), total bacterial count (TBC) and total fungal count (TFC). Occupants’ behaviors in Malaysian public hospital OPD are assessed using observation forms, and results were analyzed. Descriptive statistics were performed to characterize all study variables, whereas non-parametric Spearman Rank correlation analysis was used to assess the correlation between IAQ and occupants’ behavior. Results: After adjusting for potential cofounder, the study has suggested that occupants’ movement in new building, like seated quietly, is significantly correlated with AV in new building (r 0.642, p-value 0.010), CO2 in new (r 0.772, p-value <0.001) and old building (r -0.559, p-value 0.020), TBC in new (r 0.747, p-value 0.001) and old building (r -0.559, p-value 0.020), and TFC in new (r 0.777, p-value <0.001) and old building (r -0.485, p-value 0.049). In addition, standing relaxed movement is correlated with indoor air temperature (r 0.823, p-value <0.001) in new building, CO2 (r 0.559, p-value 0.020), TBC (r 0.559, p-value 0.020), and TFC (r -0.485, p-value 0.049) in old building, while walking is correlated with AV in new building (r -0.642, p-value 0.001), CO2 in new (r -0.772, p-value <0.001) and old building (r 0.559, p-value 0.020), TBC in new (r -0.747, p-value 0.001) and old building (r 0.559, p-value 0.020), and TFC in old building (r -0.485, p-value 0.049). The indoor air temperature is significantly correlated with number of doors kept opened (r 0.522, p-value 0.046), frequency of door adjustments (r 0.753, p-value 0.001), number of windows kept opened (r 0.522, p-value 0.046), number of air-conditioned (AC) switched on (r 0.698, p-value 0.004) and frequency of AC adjustment (r 0.753, p-value 0.001) in new hospital OPD building. AV is found to be significantly correlated with number of doors kept opened (r 0.642, p-value 0.01), frequency of door adjustments (r 0.553, p-value 0.032), number of windows kept opened (r 0.642, p-value 0.01), and frequency of AC adjustment, number of fans switched on, and frequency of fans adjustment(all with r 0.553, p-value 0.032) in new building. In old hospital OPD building, the number of doors kept opened is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), frequency of door adjustment is significantly correlated with CO₂, TBC (both r-0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of windows kept opened is significantly correlated with CO₂, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), frequency of window adjustment is significantly correlated with CO₂,TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of AC switched on is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049),, frequency of AC adjustment is significantly correlated with CO2 (r 0.559, p-value 0.020), TBC (0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of fans switched on is significantly correlated with CO2, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), and frequency of fans adjustment is significantly correlated with CO2, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049). Conclusion: This study provided evidence on IAQ parameters in Malaysian public hospitals OPD and significant factors that may be effective targets of prospective intervention, thus enabling stakeholders to develop appropriate policies and programs to mitigate IAQ issues in Malaysian public hospitals OPD.

Keywords: outpatient department, iaq, occupants practice, public hospital

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Authors: G. Malumbela, E. U. Masuku

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The economy of Botswana has increased extensively since its independence. In contrast to this increase, the construction industry which is one of the key indicators of a developing nation continues to be highly dependent on imported building material products from the neighbouring countries of South Africa, Namibia, Zimbabwe, and Zambia. Only two companies in the country currently blend cement. Even then, the overwhelming majority of raw materials used in the blends are imported. Furthermore, there are no glass manufacturers in Botswana. The ceramic industry is limited to the manufacture of clay bricks notwithstanding a few studios on crockery and sanitary ware which nonetheless use imported clay. This paper presents natural resources and industrial waste products in Botswana that can be used for the development of sustainable building materials. It also investigates at the distribution and cost of other widely used building materials in the country. Finally, the present paper looks at projects and national strategies aimed at a country-wide development of a sustainable building materials industry together with their successes and hitches.

Keywords: Botswana construction industry, construction materials, natural resources, sustainable materials

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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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: 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: Maha Bakkari, Fatiha Lemmeni, Rachid Tadili

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In this work, we present some characteristics of the furnace studied, its operating principle and the experimental measurements of the evolutions of the temperatures inside and outside the walls of the This work deals with the problem of energy consumption of pottery kilns whose energy consumption is relatively too high. In this work, we determined the sources of energy loss by studying the heat transfer of a pottery furnace, we proposed a recovery system to reduce energy consumption, and then we developed a numerical model modeling the transfers through the walls of the furnace and to optimize the insulation (reduce heat losses) by testing multiple insulators. The recovery and reuse of energy recovered by the recovery system will present a significant gain in energy consumption of the oven and cooking time. This research is one of the solutions that helps reduce the greenhouse effect of the planet earth, a problem that worries the world.

Keywords: recovery lost energy, energy efficiency, modeling, heat transfer

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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: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Balogun Azeez Olawale, Azeez S. A.

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Post occupancy evaluation (POE) is a process of assessing building performance for its users and intended function during the occupation. User satisfaction impacts the performance of educational environments and their users: students, faculty, and staff. In addition, buildings are maintained and managed by teams that spend a large amount of time and capital on their long-term sustenance. By evaluating the feedback from users of higher education facilities, university planning departments are more prepared to understand the inputs for programming and future project planning. In addition, university buildings will be closer to meeting user and maintenance needs. This paper reports on a research team made up of academics, facility personnel, and users that have developed a plan to improve the quality of campus facilities through a POE exercise on a recently built project. This study utilized a process of focus group interviews representing the different users and subsequent surveys. The paper demonstrates both the theory and practice of POE in higher education and learning environment through the case example of four universities in Nigeria's POE exercise.

Keywords: post occupancy evaluation, building performance, building analysis, building evaluation, quality control, building assessment, facility management, design quality

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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: Roghieh Eskandari, Ali Motamedi

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There is a significant demand for renovation as-built assets are aging. To plan for a desirable and comfortable indoor environment, stakeholders use simulation technics to assess potential renovation scenarios with the innovative designs. Diminished Reality (DR), which is a technique of visually removing unwanted objects from the real-world scene in real-time, can contribute to the renovation design visualization for stakeholders by removing existing structures and assets from the scene. Using DR, the objects to be demolished or changed will be visually removed from the scene for a better understanding of the intended design scenarios for stakeholders. This research proposes an integrated system for renovation plan visualization using Building Information Modelling (BIM) data and mixed reality (MR) technologies. It presents a BIM-based DR method that utilizes a textured BIM model of the environment to accurately register the virtual model of the occluded background to the physical world in real-time. This system can facilitate the simulation of the renovation plan by visually diminishing building elements in an indoor environment.

Keywords: diminished reality, building information modelling, mixed reality, stock renovation

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Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

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In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

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Authors: Hanan A. Anwar

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This paper introduces green building construction in Egypt with different concepts and practices. The following study includes green building applied definition, guidelines, regulations and Standards. Evaluation of cost/benefit of green construction methods and green construction rating systems are presented. Relevant case studies will be reviewed. Four sites will be included.

Keywords: green construction, ecofreindly, self-sufficient town, carbon neutral atmosphere

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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: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Imad Eddine Charif, Wafaa Benchouk, Sidi Mohamed Mekelleche

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The regioselectivity of a series of 16 1,3-dipolar cycloaddition reactions of nitrile oxides with 2(5H)-furanones has been analysed by means of global and local electrophilic and nucleophilic reactivity indices using density functional theory at the B3LYP level together with the 6-31G(d) basis set. The local electrophilicity and nucleophilicity indices, based on Fukui and Parr functions, have been calculated for the terminal sites, namely the C1 and O3 atoms of the 1,3-dipole and the C4 and C5 atoms of the dipolarophile. These local indices were calculated using both Mulliken and natural charges and spin densities. The results obtained show that the C5 atom of the 2(5H)-furanones is the most electrophilic site whereas the O3 atom of the nitrile oxides is the most nucleophilic centre. It turns out that the experimental regioselectivity is correctly reproduced, indicating that both Fukui- and Parr-based indices are efficient tools for the prediction of the regiochemistry of the studied reactions and could be used for the prediction of newly designed reactions of the same kind.

Keywords: 1, 3-dipolar cycloaddition, density functional theory, nitrile oxides, regioselectivity, reactivity indices

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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: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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Authors: Hanan Fayez Hussein

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‘Due to increasing environmental challenges and security problems in the world such as global warming, storms, and terrorism’, humans have discovered new technologies and new materials in order to program daily life. As providing physical and psychological security is one of the primary functions of architecture, so in order to provide security, building must prevents unauthorized entry and harm to occupant and reduce the threat of attack by making building less attractive targets by new technologies such as; Nanotechnology, which has emerged as a major science and technology focus of the 21st century and will be the next industrial revolution. Nanotechnology is control of the properties of matter, and it deals with structures of the size 100 nanometers or smaller in at least one dimension and has wide application in various fields. The construction and architecture sectors were among the first to be identified as a promising application area for nanotechnology. The advantages of using nanomaterials in construction are enormous, and promises heighten building security by utilizing the strength of building materials to make our buildings more secure and get smart home. Access barriers such as wall and windows could incorporate stronger materials benefiting from nano-reinforcement utilizing nanotubes and nano composites to act as protective cover. Carbon nanotubes, as one of nanotechnology application, can be designed up to 250 times stronger than steel. Nano-enabled devices and materials offer both enhanced and, in some cases, completely new defence systems. In the addition, the small amount of carbon nanoparticles to the construction materials such as; cement, concrete, wood, glass, gypson, and steel can make these materials act as defence elements. This paper highlights the fact that nanotechnology can impact the future global security and how building’s envelop can act as a defensive cover for the building and can be resistance to any threats can attack it. Then focus on its effect on construction materials such as; Concrete can obtain by nanoadditives excellent mechanical, chemical, and physical properties with less material, which can acts as a precautionary shield to the building.

Keywords: nanomaterial, global warming, building security, smart homes

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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

Abstract:

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.

Keywords:

Procedia PDF Downloads 510

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

The rapid growth of telehealth Internet of Things (IoT) devices has raised concerns about energy consumption and efficient data processing. This paper introduces an energy-efficient model that integrates telehealth IoT devices with a fog and cloud computing-based platform, offering a sustainable and robust solution to overcome these challenges. Our model employs fog computing as a localized data processing layer while leveraging cloud computing for resource-intensive tasks, significantly reducing energy consumption. We incorporate adaptive energy-saving strategies. Simulation analysis validates our approach's effectiveness in enhancing energy efficiency for telehealth IoT systems integrated with localized fog nodes and both private and public cloud infrastructures. Future research will focus on further optimization of the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability in other healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Rakhyun Kim, Sungho Tae

Abstract:

Global environmental issues such as abnormal weathers due to global warming, resource depletion, and ecosystem distortions have been escalating due to rapid increase of population growth, and expansion of industrial and economic development. Accordingly, initiatives have been implemented by many countries to protect the environment through indirect regulation methods such as Environmental Product Declaration (EPD), in addition to direct regulations such as various emission standards. Following this trend, life cycle assessment (LCA) techniques that provide quantitative environmental information, such as Human Toxicity Potential (HTP), for buildings are being developed in the construction industry. However, at present, the studies on the environmental database of building materials are not sufficient to provide this support adequately. The purpose of this study is to analysis human toxicity potential of major building material production stage using life cycle assessment. For this purpose, the theoretical consideration of the life cycle assessment and environmental impact category was performed and the direction of the study was set up. That is, the major material in the global warming potential view was drawn against the building and life cycle inventory database was selected. The classification was performed about 17 kinds of substance and impact index, such as human toxicity potential, that it specifies in CML2001. The environmental impact of analysis human toxicity potential for the building material production stage was calculated through the characterization. Meanwhile, the environmental impact of building material in the same category was analyze based on the characterization impact which was calculated in this study. In this study, establishment of environmental impact coefficients of major building material by complying with ISO 14040. Through this, it is believed to effectively support the decisions of stakeholders to improve the environmental performance of buildings and provide a basis for voluntary participation of architects in environment consideration activities.

Keywords: human toxicity potential, major building material, life cycle assessment, production stage

Procedia PDF Downloads 116

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

Procedia PDF Downloads 193