Search results for: building energy prediction

Authors: S. Srinivasan, E. Cretu

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The information flow (e.g. block-diagram or signal flow graph) paradigm for the design and simulation of Microelectromechanical (MEMS)-based systems allows to model MEMS devices using causal transfer functions easily, and interface them with electronic subsystems for fast system-level explorations of design alternatives and optimization. Nevertheless, the physical bi-directional coupling between different energy domains is not easily captured in causal signal flow modeling. Moreover, models of fundamental components acting as building blocks (e.g. gap-varying MEMS capacitor structures) depend not only on the component, but also on the specific excitation mode (e.g. voltage or charge-actuation). In contrast, the energy flow modeling paradigm in terms of generalized across-through variables offers an acausal perspective, separating clearly the physical model from the boundary conditions. This promotes reusability and the use of primitive physical models for assembling MEMS devices from primitive structures, based on the interconnection topology in generalized circuits. The physical modeling capabilities of Simscape have been used in the present work in order to develop a MEMS library containing parameterized fundamental building blocks (area and gap-varying MEMS capacitors, nonlinear springs, displacement stoppers, etc.) for the design, simulation and optimization of MEMS inertial sensors. The models capture both the nonlinear electromechanical interactions and geometrical nonlinearities and can be used for both small and large signal analyses, including the numerical computation of pull-in voltages (stability loss). Simscape behavioral modeling language was used for the implementation of reduced-order macro models, that present the advantage of a seamless interface with Simulink blocks, for creating hybrid information/energy flow system models. Test bench simulations of the library models compare favorably with both analytical results and with more in-depth finite element simulations performed in ANSYS. Separate MEMS-electronic integration tests were done on closed-loop MEMS accelerometers, where Simscape was used for modeling the MEMS device and Simulink for the electronic subsystem.

Keywords: across-through variables, electromechanical coupling, energy flow, information flow, Matlab/Simulink, MEMS, nonlinear, pull-in instability, reduced order macro models, Simscape

Procedia PDF Downloads 118

Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

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Now a days (Ga, Mn) is one of the most extensively studied and best understood diluted magnetic semiconductors. Also, the study of (Ga, Mn)As is a fervent research area since it allows to explore of a variety of novel functionalities and spintronics concepts that could be implemented in the future. In this work, we will calculate the energy gap of (Ga, Mn)As using the eight-band model. In the Hamiltonian, the effects of spin-orbit, spin-splitting, and strain will be considered. The dependence of the energy gap on Mn content, and the effect of the strain, which is varied continuously from tensile to compressive, will be studied. Finally, analytical expressions for the (Ga, Mn)As energy band gap, taking into account both parameters (Mn concentration and strain), will be provided.

Keywords: energy gap, diluted magnetic semiconductors, k.p method, strain

Procedia PDF Downloads 102

Authors: Shyam, G. N. Tiwari

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Energy matrices of flate plate water collectors partially covered by PV module have been estimated in the present study. Photovoltaic thermal (PVT) water collector assembly is consisting of 5 water collectors having 2 m^2 area which are partially covered by photovoltaic module at its lower portion (inlet) and connected in series. The annual overall thermal energy and exergy are computed by using climatic data of New Delhi provided by Indian Meteorological Department (IMD) Pune, India. The Energy payback time on overall thermal and exergy basis are found to be 1.6 years and 17.8 years respectively. For 25 years of life time of system the energy production factor and life cycle conversion efficiency are estimated to be 15.8 and 0.04 respectively on overall thermal energy basis whereas for the same life time the energy production factor and life cycle conversion efficiency on exergy basis are obtained as 1.4 and 0.001.

Keywords: overall thermal energy, exergy, energy payback time, PVT water collectors

Procedia PDF Downloads 359

Authors: Vasujeet Singh, Pruthiviraj Nemalipuri, Vivek Vitankar, Harish Chandra Das

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For the correct prediction of thermal and hydraulic performance (bed voidage, suspension density, pressure drop, heat transfer, and combustion kinetics), one should incorporate the correct parameters in the computational fluid dynamics simulation of a fluidized bed gasifier. Scarcity of fossil fuels, and to fulfill the energy demand of the increasing population, researchers need to shift their attention to the alternative to fossil fuels. The current research work focuses on hydrodynamics behavior and gasification of sawdust inside a 2D industrial scale FBG using the Eulerian-Eulerian multifluid model. The present numerical model is validated with experimental data. Further, this model extended for the prediction of gasification characteristics of sawdust by incorporating eight heterogeneous moisture release, volatile cracking, tar cracking, tar oxidation, char combustion, CO₂ gasification, steam gasification, methanation reaction, and five homogeneous oxidation of CO, CH₄, H₂, forward and backward water gas shift (WGS) reactions. In the result section, composition of gasification products is analyzed, along with the hydrodynamics of sawdust and sand phase, heat transfer between the gas, sand and sawdust, reaction rates of different homogeneous and heterogeneous reactions is being analyzed along the height of the domain.

Keywords: devolatilization, Eulerian-Eulerian, fluidized bed gasifier, mathematical modelling, sawdust gasification

Procedia PDF Downloads 90

Authors: Sandesh Achar

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The cloud computing industry has set new goals for better service delivery and deployment, so anyone can access services such as computation, application, and storage anytime. Cloud computing promises new possibilities for approaching sustainable solutions to deploy and advance their services in this distributed environment. This work explores energy-efficient approaches and how cloud-based architecture can reduce energy consumption levels amongst enterprises leveraging cloud computing services. Adopting cloud-based networking, database, and server machines provide a comprehensive means of achieving the potential gains in energy efficiency that cloud computing offers. In energy-efficient cloud computing, virtualization is one aspect that can integrate several technologies to achieve consolidation and better resource utilization. Moreover, the Green Cloud Architecture for cloud data centers is discussed in terms of cost, performance, and energy consumption, and appropriate solutions for various application areas are provided.

Keywords: greener cloud, cloud computing, energy efficiency, energy consumption, metadata tags, green cloud advisor

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: A. Brahma

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The drying of hydraulics materials is unavoidable and conducted to important spontaneous deformations. In this study, we show that it is possible to describe the drying shrinkage of the high-performance concrete by a simple expression. A multiple regression model was developed for the prediction of the drying shrinkage of the high-performance concrete. The assessment of the proposed model has been done by a set of statistical tests. The model developed takes in consideration the main parameters of confection and conservation. There was a very good agreement between drying shrinkage predicted by the multiple regression model and experimental results. The developed model adjusts easily to all hydraulic concrete types.

Keywords: hydraulic concretes, drying, shrinkage, prediction, modeling

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Authors: Ibrahim Yerima Gwalem, Jamila Ahmed Buhari

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In recent years, there has been an alarming rate of increase in the costs of building materials in Nigeria, and this ugly phenomenon threatens the contributions of the construction industry in national development. The purpose of this study was to assess the effects of the rising cost of building materials in Adamawa State Nigeria. Four research questions in line with the purpose of the study were raised to guide the study. Two null hypotheses were formulated and tested at 0.05 level of significance. The study adopted a survey research design. The population of the study comprises registered contractors, registered builders, selected merchants, and consultants in Adamawa state. Data were collected using researcher designed instrument tagged effects of the rising cost of building materials questionnaire (ERCBMQ). The instrument was subjected to face and content validation by two experts, one from Modibbo Adama University of Technology Yola and the other from Federal Polytechnic Mubi. The reliability of the instrument was determined by the Cronbach Alpha method and yielded a reliability index of 0.85 high enough to ascertain the reliability. Data collected from a field survey of 2019 was analyzed using mean and percentage. The means of the prices were used in the calculations of price indices and rates of inflation on building materials. Findings revealed that factors responsible for the rising cost of building materials are the exchange rate of the Nigeria Naira with a mean rating (MR) = 4.4; cost of fuel and power supply, MR = 4.3; and changes in government policies and legislation, MR = 4.2, while fluctuations in the construction cost with MR = 2.8; reduced volume of construction output, MR = 2.52; and risk of project abandonment, MRA = 2.51, were the three effects. The study concluded that adverse effects could result in a downward effect on the contributions of the construction industries on the gross domestic product (GDP) in the nation’s economy. Among the recommendations proffered include that the government should formulate a policy that will play down the agitations on the use of imported building materials by encouraging research in the production of local building materials.

Keywords: effects, rising, cost, building, materials

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

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Authors: Chaluntorn Vichasilp, Sutee Wangtueai

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This study aims to develop a new method to detect active compounds in Thai herbs (1-deoxynojirimycin (DNJ) in mulberry leave, anthocyanin in Mao and curcumin in turmeric) using near infrared spectroscopy (NIRs). NIRs is non-destructive technique that rapid, non-chemical involved and low-cost determination. By NIRs and chemometrics technique, it was found that the DNJ prediction equation conducted with partial least square regression with cross-validation had low accuracy R2 (0.42) and SEP (31.87 mg/100g). On the other hand, the anthocyanin prediction equation showed moderate good results (R2 and SEP of 0.78 and 0.51 mg/g) with Multiplication scattering correction at wavelength of 2000-2200 nm. The high absorption could be observed at wavelength of 2047 nm and this model could be used as screening level. For curcumin prediction, the good result was obtained when applied original spectra with smoothing technique. The wavelength of 1400-2500 nm was created regression model with R2 (0.68) and SEP (0.17 mg/g). This model had high NIRs absorption at a wavelength of 1476, 1665, 1986 and 2395 nm, respectively. NIRs showed prospective technique for detection of some active compounds in Thai herbs.

Keywords: anthocyanin, curcumin, 1-deoxynojirimycin (DNJ), near infrared spectroscopy (NIRs)

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Authors: Amrutha Kishor

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Today, with the rising global warming and depletion of resources every industry is moving toward sustainability and energy efficiency. As part of this movement, it is nowadays obligatory for architects to play their part by creating energy predictions for their designs. But in a lot of cases, these predictions do not reflect the real quantities of energy in newly built buildings when operating. These can be described as ‘Energy Performance Gaps’. This study aims to determine the underlying reasons for these gaps. Seven houses designed by Allan Joyce Architects, UK from 1998 until 2019 were considered for this study. The data from the residents’ energy bills were cross-referenced with the predictions made with the software SefairaPro and from energy reports. Results indicated that the predictions did not match the actual energy usage. An account of how energy was used in these seven houses was made by means of personal interviews. The main factors considered in the study were occupancy patterns, heating systems and usage, lighting profile and usage, and appliances’ profile and usage. The study found that the main reasons for the creation of energy gaps were the discrepancies in occupant usage and patterns of energy consumption that are predicted as opposed to the actual ones. This study is particularly useful for energy-conscious architectural firms to fine-tune the approach to designing houses and analysing their energy performance. As the findings reveal that energy usage in homes varies based on the way residents use the space, it helps deduce the most efficient technological combinations. This information can be used to set guidelines for future policies and regulations related to energy consumption in homes. This study can also be used by the developers of simulation software to understand how architects use their product and drive improvements in its future versions.

Keywords: architectural simulation, energy efficient design, energy performance gaps, environmental design

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Authors: Eze R. Onukwugha

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The presence of cyanide in wastewater is known to inhibit the normal functioning of bio-reactors since it has the tendency to poison reactor micro-organisms. Bench scale models of activated sludge reactors with varying aspect ratios were operated for the treatment of cassava wastewater at several values of hydraulic retention time (HRT). The different values of HRT were achieved by the use of a peristaltic pump to vary the rate of introduction of the wastewater into the reactor. The main parameters monitored are the cyanide concentration and respective COD values of the influent and effluent. These observed values were then transformed into a mathematical model for the prediction of treatment efficiency.

Keywords: wastewater, aspect ratio, cyanide-inhibited wastewater, modeling

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Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

Procedia PDF Downloads 446

Authors: Chakshu Baweja, Ishaan Prakash, Deepak Giri, Prithwish Mukherjee, Herambraj Ashok Nalawade

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The need to prevent and control rampant and indiscriminate usage of energy in present-day realm on earth has motivated active research efforts aimed at understanding of controlling mechanisms leading to sustained energy. Although much has been done but complexity of the problem has prevented a complete understanding due to nonlinear interaction between flow, heat and mass transfer in terrestrial environment. Therefore, there is need for a systematic study to clearly understand mechanisms controlling energy-spreading phenomena to increase a system’s efficiency. The present work addresses the issue of sustaining energy and proposes a devoted technique of optimizing energy in the automotive domain. The proposed method focus on utilization of the mechanical and thermal energy of an automobile IC engine by converting and storing energy due to motion of a piston in form of electrical energy. The suggested technique utilizes piston motion of the engine to generate high potential difference capable of working as a secondary power source. This is achieved by the use of a gear mechanism and a flywheel.

Keywords: internal combustion engine, energy, electromagnetic induction, efficiency, gear ratio, hybrid vehicle, engine shaft

Procedia PDF Downloads 453

Authors: P. Góes, J. Manzi

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This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

Procedia PDF Downloads 390

Authors: Wiwat Onnakklum

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Clarification is the turbidity removal process of water treatment plant. This paper was to study the factors affecting on energy consumption in order to control energy saving strategy. The factors studied were raw water turbidity in the range of 26-40 NTU and production rate in the range of 3.76-5.20 m³/sec. Clarifiers were sludge blanket and sludge recirculation clarifier. Experimental results found that the raw water turbidity was not affected significantly by energy consumption, while the production rate was affected significantly by energy consumption. Sludge blanket clarifier provided lower energy consumption than sludge recirculation clarifier about 32-37%. Subsequently, the operating pattern in production rate can be arranged to decreased energy consumption. The results showed that it can be reduced about 5.09 % of energy saving of clarification process about 754,655 Baht per year.

Keywords: sludge blanket clarifier, sludge recirculation clarifier, water treatment plant, energy

Procedia PDF Downloads 301

Authors: Tayyab Ahmad, Gerard Healey

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Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

Procedia PDF Downloads 213

Authors: Shama Urooj

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The present work investigates the relationship among financial inclusion, modernization, and energy performance in SCO member countries during the years 2011–2021. PCA is used to create composite indexes of financial inclusion, modernization, and energy performance. We used panel regression models that are both reliable and heteroscedasticity-consistent to look at the relationship among variables. The findings indicate that financial inclusion (FI) and modernization, along with the increased FDI, all appear to contribute to the energy performance in the SCO member countries. However, per capita GDP has a negative impact on energy performance. These results are unbiased and consistent with the robust results obtained by applying different econometric models. Feasible Generalized Least Square (FGLS) estimation is also used for checking the uniformity of the main model results. This research work concludes that there has been no policy coherence in SCO member countries regarding the coordination of growing financial inclusion and modernization for energy sustainability in recent years. In order to improve energy performance with modern development, policies regarding financial inclusion and modernization need be integrated both at national as well as international levels.

Keywords: financial inclusion, energy performance, modernization, technological development, SCO.

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Authors: S. Doyle, G. A. Aggidis

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Wave energy converter technologies continue to show good progress in worldwide research. One of the most researched technologies, the Oscillating Water Column (OWC), is arguably one of the most popular categories within the converter technologies due to its robustness, simplicity and versatility. However, the versatility of the OWC is still largely untapped with most deployments following similar trends with respect to applications and operating systems. As the competitiveness of the energy market continues to increase, the demand for wave energy technologies to be innovative also increases. For existing wave energy technologies, this requires identifying areas to diversify for lower costs of energy with respect to applications and synergies or integrated systems. This paper provides a review of all OWCs systems integrated into alternative applications in the past and present. The aspects and variation in their design, deployment and system operation are discussed. Particular focus is given to the Multi-OWCs (M-OWCs) and their great potential to increase capture on a larger scale, especially in synergy applications. It is made clear that these steps need to be taken in order to make wave energy a competitive and viable option in the renewable energy mix as progression to date shows that stand alone single function devices are not economical. Findings reveal that the trend of development is moving toward these integrated applications in order to reduce the Levelised Cost of Energy (LCOE) and will ultimately continue in this direction in efforts to make wave energy a competitive option in the renewable energy mix.

Keywords: wave energy converter, oscillating water column, ocean energy, renewable energy

Procedia PDF Downloads 117

Authors: Mina Rouhollahi, J. Boland

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Changes in cities’ heat balance due to rapid urbanization and the urban heat island (UHI) have increased energy demands for space cooling and have resulted in uncomfortable living conditions for urban residents. Climate resilience and comfortable living spaces can be addressed through well-designed urban development. The sustainable housing can be more effective in controlling high levels of urban heat. In Australia, to mitigate the effects of UHIs and summer heat waves, one solution to sustainable housing has been the trend to compact housing design and the construction of energy efficient dwellings. This paper analyses whether current housing configurations and orientations are effective in avoiding increased demands for air conditioning and having an energy efficient residential neighborhood. A significant amount of energy is consumed to ensure thermal comfort in houses. This paper reports on the modelling of heat transfer within the homes using the measurements of radiation, convection and conduction between exterior/interior wall surfaces and outdoor/indoor environment respectively. The simulation was tested on selected 7.5-star energy efficient houses constructed of typical material elements and insulation in Adelaide, Australia. The chosen design dwellings were analyzed in extremely hot weather through one year. The data were obtained via a thermal circuit to accurately model the fundamental heat transfer mechanisms on both boundaries of the house and through the multi-layered wall configurations. The formulation of the Lumped capacitance model was considered in discrete time steps by adopting a non-linear model method. The simulation results focused on the effects of orientation of the solar radiation on the dynamic thermal characteristics of the houses orientations. A high star rating did not necessarily coincide with a decrease in peak demands for cooling. A more effective approach to avoid increasing the demands for air conditioning and energy may be to integrate solar–climatic data to evaluate the performance of energy efficient houses.

Keywords: energy-efficient residential building, heat transfer, neighborhood orientation, solar–climatic data

Procedia PDF Downloads 119

Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert

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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.

Keywords: damping, energy-based seismic design, hysteretic energy, input energy

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Authors: Samuel Fernandes, Dylan Kato, Emin Burak Onat, Patrick Keyantuo, Raja Sengupta, Amine Bouzaghrane

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The COVID-19 pandemic has spread across the United States, forcing cities to impose stay-at-home and shelter-in-place orders. Building operations had to adjust as non-essential personnel worked from home. But as buildings prepare for personnel to return, they need to plan for safe operations amid new COVID-19 guidelines. In this paper we propose a methodology for capacity and flow modeling of personnel within buildings to safely operate under COVID-19 guidelines. We model personnel flow within buildings by network flows with queuing constraints. We study maximum flow, minimum cost, and minimax objectives. We compare our network flow approach with a simulation model through a case study and present the results. Our results showcase various scenarios of how buildings could be operated under new COVID-19 guidelines and provide a framework for building operators to plan and operate buildings in this new paradigm.

Keywords: network analysis, building simulation, COVID-19

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: Alan Lai, Wilson Yik

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With rapid urbanization, there has been a dramatic increase in global urban population in Asia and over half of population in Asia will live in urban regions in the near future. Facing with increasing exposure to climate-related stresses and shocks, most of the Asian cities will very likely to experience more frequent heat waves and flooding with rising sea levels, particularly the coastal cities will grapple for intense typhoons and storm surges. These climate changes have severe impacts in urban areas at the costs of infrastructure and population, for example, human health, wellbeing and high risks of dengue fever, malaria and diarrheal disease. With the increasing prominence of adaptation to climate changes, there have been changes in corresponding policies. Smaller cities have greater potentials for integrating the concept of resilience into their infrastructure as well as keeping pace with their rapid growths in population. It is therefore important to explore the potentials of Asian cities adapting to climate change and the opportunities of building climate resilience in urban planning and building design. Furthermore, previous studies have mainly attempted at exploiting the potential of resilience on a macro-level within urban planning rather than that on micro-level within the context of individual building. The resilience of individual building as a research field has not yet been much explored. Nonetheless, recent studies define that the resilience of an individual building is the one which is able to respond to physical damage and recover from such damage in a quickly and cost-effectively manner, while maintain its primary functions. There is also a need to develop an assessment tool to evaluate the resilience on building scale which is still largely uninvestigated as it should be regarded as a basic function of a building. Due to the lack of literature reporting metric for assessing building resilience with sustainability, the research will be designed as a case study to provide insight into the issue. The aim of this research project is to encourage and assist in developing neighborhood climate resilience design strategies for Hong Kong so as to bridge the gap between difference scales and that between theory and practice.

Keywords: resilience cities, building resilience, resilient buildings and infrastructure, climate resilience, hot and humid southeast area, high-density cities

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Authors: Mustafa A. Al-Refai

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This paper investigates the energy storage technologies that can potentially enhance the use of solar energy. Water electrolysis systems are seen as the principal means of producing a large amount of hydrogen in the future. Starting from the analysis of the models of the system components, a complete simulation model was realized in the Matlab-Simulink environment. Results of the numerical simulations are provided. The operation of electrolysis and photovoltaic array combination is verified at various insulation levels. It is pointed out that solar cell arrays and electrolysers are producing the expected results with solar energy inputs that are continuously varying.

Keywords: electrolyzer, simulink, solar energy, storage system

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Authors: Ryota Sugino, Satoshi Mizoguchi, Koji Kimita, Keiichi Muramatsu, Tatsunori Matsui, Yoshiki Shimomura

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Improving added value and productivity of services entails improving both value-in-exchange and value-in-use. Value-in-use is realized by value co-creation, where providers and receivers create value together. In higher education services, value-in-use comes from learners achieving learning outcomes (e.g., knowledge and skills) that are consistent with their learning goals. To enhance the learning outcomes of a learner, it is necessary to enhance and utilize the abilities of the teacher along with the abilities of the learner. To do this, however, the learner and the teacher need to build a consensus about their respective roles. Teachers need to provide effective learning content; learners need to choose the appropriate learning strategies by using the learning content through consensus building. This makes consensus building an important factor in value co-creation. However, methods to build a consensus about their respective roles may not be clearly established, making such consensus difficult. In this paper, we propose some strategies for consensus building between a teacher and a learner in value co-creation. We focus on a teacher and learner co-design and propose an analysis method to clarify a collaborative design process to realize value co-creation. We then analyze some counseling data obtained from a university class. This counseling aimed to build a consensus for value-in-use, learning outcomes, and learning strategies between the teacher and the learner.

Keywords: consensus building, value co-creation, higher education, learning service

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Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: A. Saccani, I. Lancellotti, E. Bursi

Abstract:

Scraps deriving from the production of epoxy-carbon fibers composites have been recycled as a reinforcement to produce building materials. Short chopped fibers (5-7 mm length) have been added at low volume content (max 10%) to produce mortars. The microstructure, mechanical properties (mainly flexural strength) and dimensional stability of the derived materials have been investigated. Two different types of matrix have been used: one based on conventional Portland Cement and the other containing geopolymers formed starting from activated metakaolin and fly ashes. In the second case the materials is almost completely made of recycled ingredients. This is an attempt to produce reliable materials solving waste disposal problems. The first collected results show promising results.

Keywords: building materials, carbon fibres, fly ashes, geopolymers

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Authors: Viriyavudh Sim, WooYoung Jung

Abstract:

Window system in high rise building is occasionally subjected to an excessive wind intensity, particularly during typhoon. The failure of window system did not affect overall safety of structural performance; however, it could endanger the safety of the residents. In this paper, comparison of fragility curves for window system of two residential buildings was studied. The probability of failure for individual window was determined with Monte Carlo Simulation method. Then, lognormal cumulative distribution function was used to represent the fragility. The results showed that windows located on the edge of leeward wall were more susceptible to wind load and the probability of failure for each window panel increased at higher floors.

Keywords: wind fragility, window system, high rise building, wind disaster

Procedia PDF Downloads 298

Authors: Hao Yan, Xiaobing Zhang

Abstract:

The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

Procedia PDF Downloads 71