Search results for: energy consumption prediction

Authors: Mohammad Reza Taherkhani‎

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make a connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: underwater sensor networks, clustering, learning automata, energy consumption

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Authors: Hamid Reza Tabatabaiefar, Bita Mansoury, Mohammad Javad Khadivi Zand

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The current energy and climate change impacts of the residential building sector in Australia are significant. Thus, the Australian Government has introduced more stringent regulations to improve building energy efficiency. In 2006, the Australian residential building sector consumed about 11% (around 440 Petajoule) of the total primary energy, resulting in total greenhouse gas emissions of 9.65 million tonnes CO2-eq. The gas and electricity consumption of residential dwellings contributed to 30% and 52% respectively, of the total primary energy utilised by this sector. Around 40 percent of total energy consumption of Australian buildings goes to heating and cooling due to the low thermal performance of the buildings. Thermal performance of buildings determines the amount of energy used for heating and cooling of the buildings which profoundly influences energy efficiency. Employing sustainable design principles and effective use of construction materials can play a crucial role in improving thermal performance of new and existing buildings. Even though awareness has been raised, the design phase of refurbishment projects is often problematic. One of the issues concerning the refurbishment of residential buildings is mostly the consumer market, where most work consists of moderate refurbishment jobs, often without assistance of an architect and partly without a building permit. There is an individual and often fragmental approach that results in lack of efficiency. Most importantly, the decisions taken in the early stages of the design determine the final result; however, the assessment of the environmental performance only happens at the end of the design process, as a reflection of the design outcome. Finally, studies have identified the lack of knowledge, experience and best-practice examples as barriers in refurbishment projects. In the context of sustainable development and the need to reduce energy demand, refurbishing the ageing residential building constitutes a necessary action. Not only it does provide huge potential for energy savings, but it is also economically and socially relevant. Although the advantages have been identified, the guidelines come in the form of general suggestions that fail to address the diversity of each project. As a result, it has been recognised that there is a strong need to develop guidelines for optimised retrofitting of existing residential buildings in order to improve their energy performance. The current study investigates the effectiveness of different energy retrofitting techniques and examines the impact of employing those methods on energy consumption of residential brick veneer buildings in Victoria (Australia). Proposing different remedial solutions for improving the energy performance of residential brick veneer buildings, in the simulation stage, annual energy usage analyses have been carried out to determine heating and cooling energy consumptions of the buildings for different proposed retrofitting techniques. Then, the results of employing different retrofitting methods have been examined and compared in order to identify the most efficient and cost-effective remedial solution for improving the energy performance of those buildings with respect to the climate condition in Victoria and construction materials of the studied benchmark building.

Keywords: brick veneer residential buildings, building energy efficiency, climate change impacts, cost effective remedial solution, energy performance, sustainable design principles

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Pengwei Qiao, Sucai Yang, Wenxia Wei

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Soil pollution has become an important issue in China. Accurate spatial distribution prediction of pollutants with interpolation methods is the basis for soil remediation in the site. However, a relatively strong variability of pollutants would decrease the prediction accuracy. Theoretically, partition interpolation can result in accurate prediction results. In order to verify the applicability of partition interpolation for a site, benzo (b) fluoranthene (BbF) in four soil layers was adopted as the research object in this paper. IDW (inverse distance weighting)-, RBF (radial basis function)-and OK (ordinary kriging)-based partition interpolation accuracies were evaluated, and their influential factors were analyzed; then, the uncertainty and applicability of partition interpolation were determined. Three conclusions were drawn. (1) The prediction error of partitioned interpolation decreased by 70% compared to unpartitioned interpolation. (2) Partition interpolation reduced the impact of high CV (coefficient of variation) and high concentration value on the prediction accuracy. (3) The prediction accuracy of IDW-based partition interpolation was higher than that of RBF- and OK-based partition interpolation, and it was suitable for the identification of highly polluted areas at a contaminated site. These results provide a useful method to obtain relatively accurate spatial distribution information of pollutants and to identify highly polluted areas, which is important for soil pollution remediation in the site.

Keywords: accuracy, applicability, partition interpolation, site, soil pollution, uncertainty

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Authors: Mahsa Karimpour, Martin Belusko, Ke Xing, Frank Bruno

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Traditionally the embodied energy of design choices which reduce operational energy were assumed to have a negligible impact on the life cycle energy of buildings. However with new buildings having considerably lower operational energy, the significance of embodied energy increases. A life cycle assessment of a population of house designs was conducted in a mild and mixed climate zone. It was determined not only that embodied energy dominates life cycle energy, but that the impact on embodied of design choices was of equal significance to the impact on operational energy.

Keywords: building life cycle energy, embodied energy, energy design measures, low energy buildings

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Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

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The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

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Authors: Edgar Gasafi, Robert Pardemann, Linus Perander

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For the production of lithium carbonate or hydroxide out of lithium bearing ores, a thermal activation (calcination/decrepitation) is required for the phase transition in the mineral to enable an acid respectively soda leaching in the downstream hydrometallurgical section. In this paper, traditional processing in Lithium industry is reviewed, and opportunities to reduce energy consumption and improve product quality and recovery rate will be discussed. The conventional process approach is still based on rotary kiln calcination, a technology in use since the early days of lithium ore processing, albeit not significantly further developed since. A new technology, at least for the Lithium industry, is fluidized bed calcination. Decrepitation of lithium ore was investigated at Outotec’s Frankfurt Research Centre. Focusing on fluidized bed technology, a study of major process parameters (temperature and residence time) was performed at laboratory and larger bench scale aiming for optimal product quality for subsequent processing. The technical feasibility was confirmed for optimal process conditions on pilot scale (400 kg/h feed input) providing the basis for industrial process design. Based on experimental results, a comprehensive Aspen Plus flow sheet simulation was developed to quantify mass and energy flow for the rotary kiln and fluidized bed system. Results show a significant reduction in energy consumption and improved process performance in terms of temperature profile, product quality and plant footprint. The major conclusion is that a substantial reduction of energy consumption can be achieved in processing Lithium bearing ores by using fluidized bed based systems. At the same time and different from rotary kiln process, an accurate temperature and residence time control is ensured in fluidized-bed systems leading to a homogenous temperature profile in the reactor which prevents overheating and sintering of the solids and results in uniform product quality.

Keywords: calcination, decrepitation, fluidized bed, lithium, spodumene

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Authors: Balram Panjwani, Bernd Wittgens, Jan Erik Olsen, Stein Tore Johansen

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The Norwegian ferroalloy industry is a world leader in sustainable production of ferrosilicon, silicon and manganese alloys with the lowest global specific energy consumption. One of the byproducts during the metal reduction process is energy rich off-gas and usually this energy is not harnessed. A novel concept for sustainable energy recovery from ferroalloy off-gas is discussed. The concept is founded on the idea of introducing a combustion chamber in the off-gas section in which energy rich off-gas mainly consisting of CO will be combusted. This will provide an additional degree of freedom for optimizing energy recovery. A well-controlled and high off-gas temperature will assure a significant increase in energy recovery and reduction of emissions to the atmosphere. Design and operation of the combustion chamber depend on many parameters, including the total power capacity of the combustion chamber, sufficient residence time for combusting the complex Poly Aromatic Hydrocarbon (PAH), NOx, as well as converting other potential pollutants. The design criteria for the combustion chamber have been identified and discussed and sizing of the combustion chamber has been carried out considering these design criteria. Computational Fluid Dynamics (CFD) has been utilized extensively for sizing the combustion chamber. The results from our CFD simulations of the flow in the combustion chamber and exploring different off-gas fuel composition are presented. In brief, the paper covers all aspect which impacts the sizing of the combustion chamber, including insulation thickness, choice of insulating material, heat transfer through extended surfaces, multi-staging and secondary air injection.

Keywords: CFD, combustion chamber, arc furnace, energy recovery

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Authors: Zhenzhen Zhang

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As major human activity places, buildings consume a large amount of energy, and residential buildings are very important part of it. An extensive research work had been conducted to research how to achieve low energy goals, vernacular dwellings and contemporary technologies are two prime parameters among them. On one hand, some researchers concentrated on vernacular dwellings which were climate-response design and could offer a better living condition without mechanic application. On the other hand, a series concepts appeared based on modern technologies, surplus energy house, bioclimatic architecture, etc. especially thermodynamic architecture which integrates the micro-climate, human activity, thermal comfort, and energy efficiency into design. How to blend the two parameters is the key research topic now, which would act as the key to how to integrate the ancient design wise and contemporary new technologies. By several cases study, this paper will represent the evolution of thermodynamic architecture and then try to develop one methodology about how to produce a typical thermodynamic prototype for one area by blending the ancient building wise and contemporary concepts to achieve both low energy consumption and surplus energy.

Keywords: vernacular dwelling, thermodynamic architecture, bioclimatic architecture, thermodynamic prototype, surplus energy

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Authors: A. A, F. Belmir, A. El Bouari, Y. Abboud

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This article presents a study of the thermal performance of a new solar mobile refrigeration prototype for the preservation of perishable foods. The simulation of the refrigeration cycle and the calculation of the thermal balances made it possible to estimate its consumption and to evaluate the capacity of each photovoltaic component necessary for the production of energy. The study provides a description of the refrigerator construction and operation, including an energy balance analysis of the refrigerator performance under typical loads. The photovoltaic system requirements are also detailed.

Keywords: composite, material, photovoltaic, refrigeration, thermal

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Authors: Vaishali P. Joshi, Pallav Joshi

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The objective of this study is to examine the differences fashion innovators and non-fashion innovators in their fashion consumption behavior in terms of their pre-purchase behavior, purchase behavior and post purchase behavior. The questionnaire was distributed to a female college student for data collection for achieving the objective of the first part of the study. Question-related to fashion innovativeness and fashion consumption behavior was asked. The sample was comprised of 81 college females ages 18 through 30 who were attending Business Management degree. A series of attitude questions was used to categorize respondents on the Innovativeness Scale. 32 respondents with a score of 21 and above were designated as Fashion innovators and the remainder (49) as Non-fashion innovators. Findings showed that there exist significant differences between innovators and non-innovators in their fashion consumption behavior. Data was analyzed through frequency distribution table. Many differences were found in the behavior of innovators and non-innovators in terms of their pre-purchase, actual purchase, and post-purchase behavior.

Keywords: fashion, innovativeness, consumption behavior, purchase

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

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Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

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Authors: M. F. Páramo, F. Cadaveira, M. S. Rodríguez

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The first year at university is a critical period for personal-emotional and academic adjustment in emerging adults. Moreover, some studies show that alcohol consumption increases in young adults on transition to university. The main purpose of this study was to analyze the impact of hazardous alcohol consumption and gender on adjustment to university, understood as a multidimensional construct involving an array of demands. A sample of 300 first year students in Spain completed the Student Adaptation to College Questionnaire (SACQ) and the Alcohol Use Disorders Identification Test (AUDIT). Examination of the data by analysis of variance revealed that adjustment to university was lower in the students undertaking hazardous alcohol consumption than in the other students. Surprisingly, the personal-emotional adjustment of students with hazardous alcohol consumption was not lower than in the other students. Analysis of the gender effect revealed that levels of personal-emotional adjustment were higher in males than in females. This is our first study examining the influence of alcohol consumption on university adjustment. Future research should examine this relationship more closely, with the aim of designing public health strategies focused on limiting abusive consumption of alcohol in university students.

Keywords: alcohol consumption, first year university students, gender, SACQ

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Authors: Pingshan Chen, Zhiliang Dong

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In order to estimate the post-construction settlement more objectively, the power-polynomial model is proposed, which can reflect the trend of settlement development based on the observed settlement data. It was demonstrated by an actual case history of an embankment, and during the prediction. Compared with the other three prediction models, the power-polynomial model can estimate the post-construction settlement more accurately with more simple calculation.

Keywords: prediction, model, post-construction settlement, soft ground

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Authors: Sha Fan, Renuka Mahadevan

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In recent years, the subject of how retirement influences consumption behaviours has garnered attention in economic research. However, a significant gap persists in our understanding of how retirement precisely impacts tourism consumption patterns among the elderly demographic. To address this gap, this research conducts an in-depth exploration into the multifaceted relationship between retirement and elderly tourism consumption.To achieve this, the study employs regression discontinuity design, using three waves of panel data from China covering a span of six years. This approach aims to identify the causality between retirement and tourism consumption. Furthermore, the study scrutinizes the pathways through which retirement's impact on tourism consumption unfolds. It adopts a dual-pronged perspective, examining the roles played by economic status and the availability of leisure time. The economic dimension underscores the financial adjustments that retirees make as they transition into a new phase of life, impacting their propensity to allocate resources towards tourism activities. Meanwhile, considering leisure time recognizes that retirement often heralds an era of newfound freedom, allowing retirees the luxury to engage in leisurely pursuits like tourism.

Keywords: tourism consumption, retirement, the elderly, regression discontinuity design

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Authors: Silvia A. Magalhaes, Vasco P. De Freitas, Jose L. Alexandre

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Most of the European literature concerning energy efficiency and thermal comfort of dwellings assumes permanent heating and focuses on energy-saving measures. European National regulations are designed for those permanent comfort conditions. On the other hand, very few studies focus on the effect of the improvement measures in comfort reduction, for free-floating conditions or intermittent heating, in fuel poverty vulnerable countries. In Portugal, only 21% of the household energy consumptions (and 10% of the cost) are spent in space heating, while, on average European bills, this value rises to 67%. The mild climate, but mainly fuel poverty and cultural background, justifies these low heating practices. This study proposes a “passive discomfort” index definition, considering free-floating temperatures or with intermittent heating profiles (more realistic conditions), putting the focus on comfort rather than energy consumption (which is low for these countries). The aim is to compare both energy (regarding the legal framework of national regulation) and comfort (considering realistic conditions of use) to identify some correlation. It was developed an experimental campaign of indoor thermal conditions in a 19th building located in Porto with several apartments. One dwelling was chosen as a case study to carry out a sensitivity analysis. The results are discussed comparing both theoretical energy consumption (energy rates from national regulation) and discomfort (new index defined), for different insulation thicknesses, orientations, and intermittent heating profiles. The results show that the different passive options (walls insulation and glazing options) have a small impact on winter discomfort, which is always high for low heating profiles. Moreover, it was shown that the insulation thickness on walls has no influence, and the minimum insulation thickness considered is enough to achieve the same impact on discomfort reduction. Plus, for these low heating profiles, other conditions are critical, as the orientation. Finally, there isn’t an unequivocal relation between the energy label and the discomfort index. These and other results are surprising when compared with the most usual approaches, which assume permanent heating.

Keywords: dwellings in historical buildings, low-heating countries, mild climates, thermal comfort

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Authors: Yuhang Wang

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As energy is vital to industrial productivity and human existence, ensuring energy security becomes a critical government responsibility. The Chinese government has implemented the energy transition to safeguard China’s energy security. Throughout this progression, the Chinese government has faced numerous obstacles. This article seeks to describe the causes of China’s energy transition barriers and the steps taken by the Chinese government to overcome them.

Keywords: energy transition, energy market, fragmentation, path dependency

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Authors: Aparna Bhat, Rajeshwari Hegde

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Renewable energy sources also called non-conventional energy sources that are continuously replenished by natural processes. For example, solar energy, wind energy, bio-energy- bio-fuels grown sustain ably), hydropower etc., are some of the examples of renewable energy sources. A renewable energy system converts the energy found in sunlight, wind, falling-water, sea-waves, geothermal heat, or biomass into a form, we can use such as heat or electricity. Most of the renewable energy comes either directly or indirectly from sun and wind and can never be exhausted, and therefore they are called renewable. This paper presents a review about conventional and renewable energy scenario of India. The paper also presents current status, major achievements and future aspects of renewable energy in India and implementing renewable for the future is also been presented.

Keywords: solar energy, renewabe energy, wind energy, bio-diesel, biomass, feedin

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Authors: Ghada Elshafei, Abdelazim Negm

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Life cycle assessment is a technique to assess the environmental aspects and potential impacts associated with a product, process, or service, by compiling an inventory of relevant energy and material inputs and environmental releases; evaluating the potential environmental impacts associated with identified inputs and releases; and interpreting the results to help you make a more informed decision. In this paper, the life cycle assessment of aluminum and beech wood as two commonly used materials in Egypt for window frames are heading, highlighting their benefits and weaknesses. Window frames of the two materials have been assessed on the basis of their production, energy consumption and environmental impacts. It has been found that the climate change of the windows made of aluminum and beech wood window, for a reference window (1.2m × 1.2m), are 81.7 mPt and - 52.5 mPt impacts respectively. Among the most important results are: fossil fuel consumption, potential contributions to the green building effect and quantities of solid waste tend to be minor for wood products compared to aluminum products; incineration of wood products can cause higher impacts of acidification and eutrophication than aluminum, whereas thermal energy can be recovered.

Keywords: aluminum window, beech wood window, green building, life cycle assessment, life cycle analysis, SimaPro software, window frame

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Timur Zhukov, Yuko Yamashita

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Music as a product of hedonic consumption has been researched at least since the early 20th century, but little light has been shed on how language affects its consumption process. At the intersection of music consumption, language impact, and consumer behavior, this research explores the influence of language on music consumption in Japan. Its aim is to clarify how listening to music in different languages affects the listener’s purchase intention and sharing intention by conducting a survey where respondents listen to three versions of the same song in different languages in random order. It uses an existing framework that views the flow of music consumption as a combination of responses (emotional response, sensory response, imaginal response, analytical responses) affecting the experiential response, which then affects the overall affective response, followed by the need to reexperience and lastly the purchase intention. In this research, the sharing intention has been added to the model to better fit the modern consumption model (e.g., AISAS). This research shows how positive and negative emotions and imaginal and analytical responses change depending on the language and what impact it has on consumer behavior. It concludes by proposing how modern music businesses can learn from the language differences and cater to the needs of the audiences who speak different languages.

Keywords: AISAS, consumer behavior, first language, music consumption, second language

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Authors: Hiba Naccache, Rima Hleiss

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Additive manufacturing AM or 3D printing is one of the pillars of Industry 4.0. Compared to traditional manufacturing, AM provides a prototype before production in order to optimize the design and avoid the stock market and uses strictly necessary material which can be recyclable, for the benefit of leaning towards local production, saving money, time and resources. Different types of AM exist and it has a broad range of applications across several industries like aerospace, automotive, medicine, education and else. The Laser Powder Bed Fusion (LPBF) is a metal AM technique that uses a laser to liquefy metal powder, layer by layer, to build a three-dimensional (3D) object. In industry 4.0 and aligned with the numbers 9 (Industry, Innovation and Infrastructure) and 12 (Responsible Production and Consumption) of the Sustainable Development Goals of the UNESCO 2030 Agenda, the AM’s manufacturers committed to minimizing the environmental impact by being sustainable in every production. The LPBF has several environmental advantages, like reduced waste production, lower energy consumption, and greater flexibility in creating components with lightweight and complex geometries. However, LPBF also have environmental drawbacks, like energy consumption, gas consumption and emissions. It is critical to recognize the environmental impacts of LPBF in order to mitigate them. To increase awareness and promote sustainable practices regarding LPBF, the researchers use the Elaboration Likelihood Model (ELM) theory where people from multiple universities in France and Qatar process information in two ways: peripherally and centrally. The peripheral campaigns use superficial cues to get attention, and the central campaigns provide clear and concise information. The authors created a seminar including a video showing LPBF production and a website with educational resources. The data is collected using questionnaire to test attitude about the public awareness before and after the seminar. The results reflected a great shift on the awareness toward LPBF and its impact on the environment. With no presence of similar research, to our best knowledge, this study will add to the literature on the sustainability of the LPBF production technique.

Keywords: additive manufacturing, laser powder bed fusion, elaboration likelihood model theory, sustainable development goals, education-awareness, France, Qatar, specific energy consumption, environmental impact, lightweight components

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: Hafsi Khebab, Zirari Mounir, Mohamed Nadjib Bouaziz

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High Global Warming Potential refrigerants (HydroFluroCarbons) are one of the worst greenhouse gases used in a wide variety of applications, including refrigeration and air-conditioning. Nanotechnology is a promising field in sustainable energy to reduce energy and ecological resource consumption for HVACR (heat, ventilation, air conditioning, and refrigeration) systems. Most researchers reported an improvement in heat transfer coefficient, Coefficient of performance. In this report, a brief summary has been done on the performance enhancement of the Vapor Compression Refrigeration system using HFC134a with nano refrigerants.

Keywords: nanorefrigerant, HFCs, greenhouse gases, GWP, HVACR systems, energy saving

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Salman Naseer

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One of the main challenges of operating a smart city (SC) is collecting the massive data generated from multiple data sources (DS) and to transmit them to the control units (CU) for further data processing and analysis. These ever-increasing data demands require not only more and more capacity of the transmission channels but also results in resource over-provision to meet the resilience requirements, thus the unavoidable waste because of the data fluctuations throughout the day. In addition, the high energy consumption (EC) and carbon discharges from these data transmissions posing serious issues to the environment we live in. Therefore, to overcome the issues of intensive EC and carbon emissions (CE) of massive data dissemination in Smart Cities, we propose an energy efficient and carbon reduction approach by utilizing the daily mobility of the existing vehicles as an alternative communications channel to accommodate the data dissemination in smart cities. To illustrate the effectiveness and efficiency of our approach, we take the Auckland City in New Zealand as an example, assuming massive data generated by various sources geographically scattered throughout the Auckland region to the control centres located in city centre. The numerical results show that our proposed approach can provide up to 5 times lower delay as transferring the large volume of data by utilizing the existing daily vehicles’ mobility than the conventional transmission network. Moreover, our proposed approach offers about 30% less EC and CE than that of conventional network transmission approach.

Keywords: smart city, delay tolerant network, infrastructure offloading, opportunistic network, vehicular mobility, energy consumption, carbon emission

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Authors: Cedric Leong, Parth Desai, Parth Patel

Abstract:

The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

Procedia PDF Downloads 489

Authors: Omid Khabiri, Maryam Ghavami

Abstract:

Buildings designed and built as high performance, sustainable or green are the vanguard in a movement to make buildings more energy efficient and less environmentally harmful. Although Heating, Ventilating, and Air Conditioning (HVAC) systems offer many opportunities for recovery and re-use of thermal energy; however, the amount of energy used annually by these systems typically ranges from 40 to 60 percent of the overall energy consumption in a building, depending on the building design, function, condition, climate, and the use of renewable energy strategies. HVAC systems may also damage the environment by unnecessary use of non-renewable energy sources, which contribute to environmental pollution, and by creating noise and discharge of contaminated water and air containing chemicals, lubricating oils, refrigerants, heat transfer fluids, and particulate (gases matter). In fact, HVAC systems will significantly impact how “green” a building is, where an efficient HVAC system design can result in considerable energy, emissions and cost savings as well as providing increased user thermal comfort. This paper presents the basic concepts of green building design and discusses the role of efficient HVAC system and practical strategies for ensuring high performance sustainable buildings in design and operation.

Keywords: green building, hvac system, design strategies, high-performance equipment, efficient technologies

Procedia PDF Downloads 553

Authors: Narayan Prasad Adhikari

Abstract:

In Nepal, the crop residues have often been considered as one of the potential sources of energy to cope with prevailing energy crisis. However, the lack of systematic studies about production and various other competent uses of crop production is the main obstacle to evaluate net potential of the residues for energy production. Under this background, this study aims to assess the net annual availability of crop residues for energy production by undertaking three different districts with the representation of country’s three major regions of lowland, hill, and mountain. The five major cereal crops of paddy, wheat, maize, millet, and barley are considered for the analysis. The analysis is based upon two modes of household surveys. The first mode of survey is conducted to total of 240 households to obtain key information about crop harvesting and livestock management throughout a year. Similarly, the quantification of main crops along with the respective residues on fixed land is carried out to 45 households during second mode. The range of area of such fixed land is varied from 50 to 100 m2. The measurements have been done in air dry basis. The quantity for competitive uses of respective crop residues is measured on the basis of respondents’ feedback. There are four major competitive uses of crop residues at household which are building material, burning, selling, and livestock fodder. The results reveal that the net annual available crop residues per household are 4663 kg, 2513 kg, and 1731 kg in lowland, hill, and mountain respectively. Of total production of crop residues, the shares of dedicated fodder crop residues (except maize stalk and maize cob) are 94 %, 62 %, and 89 % in lowland, hill, and mountain respectively and of which the corresponding shares of fodder are 87 %, 91 %, and 82 %. The annual percapita energy equivalent from net available crop residues in lowland, hill, and mountain are 2.49 GJ, 3.42 GJ, and 0.44 GJ which represent 30 %, 33 %, and 3 % of total annual energy consumption respectively whereas the corresponding current shares of crop residues are only 23 %, 8 %, and 1 %. Hence, even utmost exploitation of available crop residues can hardly contribute to one third of energy consumption at household level in lowland, and hill whereas this is limited to particularly negligible in mountain. Moreover, further analysis has also been done to evaluate district wise supply-demand context of dedicated fodder crop residues on the basis of presence of livestock. The high deficit of fodder crop residues in hill and mountain is observed where the issue of energy generation from these residues will be ludicrous. As a contrary, the annual production of such residues for livestock fodder in lowland meets annual demand with modest surplus even if entire fodder to be derived from the residues throughout a year and thus there seems to be further potential to utilize the surplus residues for energy generation.

Keywords: crop residues, hill, lowland, mountain

Procedia PDF Downloads 446