Search results for: energy detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11613

Search results for: energy detection

9333 A Study of Structural Damage Detection for Spacecraft In-Orbit Based on Acoustic Sensor Array

Authors: Lei Qi, Rongxin Yan, Lichen Sun

Abstract:

With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

Procedia PDF Downloads 292
9332 Microwave-Assisted Torrefaction of Teakwood Biomass Residues: The Effect of Power Level and Fluid Flows

Authors: Lukas Kano Mangalla, Raden Rinova Sisworo, Luther Pagiling

Abstract:

Torrefaction is an emerging thermo-chemical treatment process that aims to improve the quality of biomass fuels. This study focused on upgrading the waste teakwood through microwave torrefaction processes and investigating the key operating parameters to improve energy density for the quality of biochar production. The experiments were carried out in a 250 mL reactor placed in a microwave cavity on two different media, inert and non-inert. The microwave was operated at a frequency of 2.45GHz with power level variations of 540W, 720W, and 900W, respectively. During torrefaction processes, the nitrogen gas flows into the reactor at a rate of 0.125 mL/min, and the air flows naturally. The temperature inside the reactor was observed every 0.5 minutes for 20 minutes using a K-Type thermocouple. Changes in the mass and the properties of the torrefied products were analyzed to predict the correlation between calorific value, mass yield, and level power of the microwave. The results showed that with the increase in the operating power of microwave torrefaction, the calorific value and energy density of the product increased significantly, while mass and energy yield tended to decrease. Air can be a great potential media for substituting the expensive nitrogen to perform the microwave torrefaction for teakwood biomass.

Keywords: torrefaction, microwave heating, energy enhancement, mass and energy yield

Procedia PDF Downloads 90
9331 Internet of Things Edge Device Power Modelling and Optimization Simulator

Authors: Cian O'Shea, Ross O'Halloran, Peter Haigh

Abstract:

Wireless Sensor Networks (WSN) are Internet of Things (IoT) edge devices. They are becoming widely adopted in many industries, including health care, building energy management, and conditional monitoring. As the scale of WSN deployments increases, the cost and complexity of battery replacement and disposal become more significant and in time may become a barrier to adoption. Harvesting ambient energies provide a pathway to reducing dependence on batteries and in the future may lead to autonomously powered sensors. This work describes a simulation tool that enables the user to predict the battery life of a wireless sensor that utilizes energy harvesting to supplement the battery power. To create this simulator, all aspects of a typical WSN edge device were modelled including, sensors, transceiver, and microcontroller as well as the energy source components (batteries, solar cells, thermoelectric generators (TEG), supercapacitors and DC/DC converters). The tool allows the user to plug and play different pre characterized devices as well as add user-defined devices. The goal of this simulation tool is to predict the lifetime of a device and scope for extension using ambient energy sources.

Keywords: Wireless Sensor Network, IoT, edge device, simulation, solar cells, TEG, supercapacitor, energy harvesting

Procedia PDF Downloads 130
9330 Deep Learning for Renewable Power Forecasting: An Approach Using LSTM Neural Networks

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 263
9329 Inadequate Intake of Energy and Nutrients: A Comparative Cross-Sectional Study Between Sport and Non-sport Science University Students of Southern Ethiopia

Authors: Beruk Berhanu Desalegn, Kebede Awgechew, Addisalem Mesfin

Abstract:

Introduction: This study aimed to investigate and compare the energy and selected nutrient intakes of sport science and non-sport science University students of Southern Ethiopia. Method: Multiple-day dietary data were collected from 166 university students (76 sport science and 90 non-sport sciences). Average daily energy and nutrient intake, and inadequate intakes were calculated using NutriSurvey (NS). Results: There were significant differences (p < 0.05) in the median intakes of energy, total carbohydrate, and vitamin B1 between female students from the sport science and non-sport science groups, but only the median intake of iron was significantly different (p < 0.05) between the male sport and non-sport science students’ group. The prevalence of inadequate intake of vitamin B1 were significantly (p<0.05) higher in the male and female from the non-sport science groups compared to the male and female students’ groups in the sport science, respectively. Whereas, the prevalence of inadequate iron intake by the male sport science students’ group was significantly (p<0.05) higher compared to their counterparts. Similarly, the prevalence of inadequate energy among the females from the sport science group was significantly (p<0.05) higher compared to the female students from the non-sport science department group. The prevalence of inadequate intakes of dietary energy, and the majority of the nutrients (protein, fat, vitamin A, B1, B2, and magnesium) were high (>50%) in selected University students. Conclusion: The energy and majority of nutrient intakes by the students in the selected universities of southern Ethiopia were sub-optimal. Therefore, activities that will improve the dietary intake of University students should include weekly meal plan revision considering their average recommended nutrient intake (RNI).

Keywords: dietary intake, sport science, University students, Ethiopia

Procedia PDF Downloads 82
9328 India’s Energy Transition, Pathways for Green Economy

Authors: B. Sudhakara Reddy

Abstract:

In modern economy, energy is fundamental to virtually every product and service in use. It has been developed on the dependence of abundant and easy-to-transform polluting fossil fuels. On one hand, increase in population and income levels combined with increased per capita energy consumption requires energy production to keep pace with economic growth, and on the other, the impact of fossil fuel use on environmental degradation is enormous. The conflicting policy objectives of protecting the environment while increasing economic growth and employment has resulted in this paradox. Hence, it is important to decouple economic growth from environmental degeneration. Hence, the search for green energy involving affordable, low-carbon, and renewable energies has become global priority. This paper explores a transition to a sustainable energy system using the socio-economic-technical scenario method. This approach takes into account the multifaceted nature of transitions which not only require the development and use of new technologies, but also of changes in user behaviour, policy and regulation. The scenarios that are developed are: baseline business as usual (BAU) as well as green energy (GE). The baseline scenario assumes that the current trends (energy use, efficiency levels, etc.) will continue in future. India’s population is projected to grow by 23% during 2010 –2030, reaching 1.47 billion. The real GDP, as per the model, is projected to grow by 6.5% per year on average between 2010 and 2030 reaching US$5.1 trillion or $3,586 per capita (base year 2010). Due to increase in population and GDP, the primary energy demand will double in two decades reaching 1,397 MTOE in 2030 with the share of fossil fuels remaining around 80%. The increase in energy use corresponds to an increase in energy intensity (TOE/US $ of GDP) from 0.019 to 0.036. The carbon emissions are projected to increase by 2.5 times from 2010 reaching 3,440 million tonnes with per capita emissions of 2.2 tons/annum. However, the carbon intensity (tons per US$ of GDP) decreases from 0.96 to 0.67. As per GE scenario, energy use will reach 1079 MTOE by 2030, a saving of about 30% over BAU. The penetration rate of renewable energy resources will reduce the total primary energy demand by 23% under GE. The reduction in fossil fuel demand and focus on clean energy will reduce the energy intensity to 0.21 (TOE/US$ of GDP) and carbon intensity to 0.42 (ton/US$ of GDP) under the GE scenario. The study develops new ‘pathways out of poverty’ by creating more than 10 million jobs and thus raise the standard of living of low-income people. Our scenarios are, to a great extent, based on the existing technologies. The challenges to this path lie in socio-economic-political domains. However, to attain a green economy the appropriate policy package should be in place which will be critical in determining the kind of investments that will be needed and the incidence of costs and benefits. These results provide a basis for policy discussions on investments, policies and incentives to be put in place by national and local governments.

Keywords: energy, renewables, green technology, scenario

Procedia PDF Downloads 248
9327 CFD Simulation Research on a Double Diffuser for Wind Turbines

Authors: Krzysztof Skiba, Zdzislaw Kaminski

Abstract:

Wind power is based on a variety of construction solutions to convert wind energy into electrical energy. These constructions are constrained by the correlation between their energy conversion efficiency and the area they occupy. Their energy conversion efficiency can be improved by wind tunnel tests of a rotor as a diffuser to optimize shapes of aerodynamic elements, to adapt these elements to changing conditions and to increase airflow intensity. This paper discusses the results of computer simulations and aerodynamic analyzes of this innovative diffuser design. The research aims at determining the aerodynamic phenomena triggered by the airflow inside this construction, and developing a design to improve the efficiency of the wind turbine. The research results enable us to design a diffuser with a double Venturi nozzle and specially shaped blades. The design of this type uses Bernoulli’s law on the behavior of the flowing medium in the tunnel of a decreasing diameter. The air flowing along the tunnel changes its velocity so the rotor inside such a decreased tunnel diameter rotates faster in this airflow than does the wind outside this tunnel, which makes the turbine more efficient. Additionally, airflow velocity is improved by applying aerodynamic rings with extended trailing edges to achieve controlled turbulent vortices.

Keywords: wind turbine, renewable energy, cfd, numerical analysis

Procedia PDF Downloads 309
9326 Implementing Biogas Technology in Rural Areas of Limpopo: Analysis of Gawula, Mopani District in South Africa

Authors: Thilivhali E. Rasimphi, David Tinarwo

Abstract:

Access to energy is crucial in poverty alleviation, economic growth, education, and agricultural improvement. The best renewable energy source is one which is locally available, affordable, and can easily be used and managed by local communities. The usage of renewable energy technology has the potential to alleviate many of the current problems facing rural areas. To address energy poverty, biogas technology has become an important part of resolving such. This study, therefore, examines the performance of digesters in Gawula village; it also identifies the contributing factors to the adoption and use of the technology. Data was collected using an open-ended questionnaire from biogas users. To evaluate the performance of the digesters, a data envelopment analysis (DEA) non-parametric technique was used, and to identify key factors affecting adoption, a logit model was applied. The reviewed critical barriers to biogas development in the area seem to be a poor institutional framework, poor infrastructure, a lack of technical support, user training on maintenance and operation, and as such, the implemented plants have failed to make the desired impact. Thus most digesters were abandoned. To create awareness amongst rural communities, government involvement is key, and there is a need for national programs. Biogas technology does what few other renewable energy technologies do, which is to integrate waste management and energy. This creates a substantial opportunity for biogas generation and penetration. That is, a promising pathway towards achieving sustainable development through biogas technology.

Keywords: domestic biogas technology, economic, sustainable, social, rural development

Procedia PDF Downloads 137
9325 DEEPMOTILE: Motility Analysis of Human Spermatozoa Using Deep Learning in Sri Lankan Population

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

Abstract:

Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

Procedia PDF Downloads 105
9324 Studies on the Feasibility of Cow Dung as a Non-Conventional Energy Source

Authors: Raj Kumar Rajak, Bharat Mishra

Abstract:

Bio-batteries represent an entirely new long-term, reasonable, reachable and ecofriendly approach to produce sustainable energy. In the present experimental work, we have studied the effect of generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow dung as an electrolyte. C-Mg electrode pair shows maximum voltage and SCC (Short Circuit Current) while C-Zn electrode pair shows less OCV (Open Circuit Voltage) and SCC. We have chosen C-Zn electrodes because Mg electrodes are not economical. By the studies of different electrodes and cow dung, it is found that C-Zn electrode battery is more suitable. This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: bio-batteries, electricity, cow-dung, electrodes, non-conventional

Procedia PDF Downloads 204
9323 Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things

Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Abstract:

Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

Procedia PDF Downloads 334
9322 Automatic Detection and Classification of Diabetic Retinopathy Using Retinal Fundus Images

Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

Procedia PDF Downloads 293
9321 Analytical Evaluation on Hysteresis Performance of Circular Shear Panel Damper

Authors: Daniel Y. Abebe, Jaehyouk Choi

Abstract:

The idea of adding metallic energy dissipaters to a structure to absorb a large part of the seismic energy began four decades ago. There are several types of metal-based devices conceived as dampers for the seismic energy absorber whereby damages to the major structural components could be minimized for both new and existing structures. This paper aimed to develop and evaluate structural performance of both stiffened and non stiffened circular shear panel damper for passive seismic energy protection by inelastic deformation. Structural evaluation was done using commercially available nonlinear FE simulation program. Diameter-to-thickness ratio is employed as main parameter to investigate the hysteresis performance of stiffened and unstiffened circular shear panel. Depending on these parameters three different buckling mode and hysteretic behavior was found: yielding prior to buckling without strength degradation, yielding prior to buckling with strength degradation and yielding with buckling and strength degradation which forms pinching at initial displacement. Hence, the hysteresis behavior is identified, specimens which deform without strength degradation so it will be used as passive energy dissipating device in civil engineering structures.

Keywords: circular shear panel damper, FE analysis, hysteretic behavior, large deformation

Procedia PDF Downloads 385
9320 Study of the Microstructural Evolution and Precipitation Kinetic in AZ91 Alloys

Authors: A. Azizi, M. Toubane, L. Chetibi

Abstract:

Differential scanning calorimetry (DSC) is a widely used technique for the study of phase transformations, particularly in the study of precipitation. The kinetic of the precipitation and dissolution is always related to the concept of activation energy Ea. The determination of the activation energy gives important information about the kinetic of the precipitation reaction. In this work, we were interested in the study of the isothermal and non-isothermal treatments on the decomposition of the supersaturated solid solution in the alloy AZ91 (Mg-9 Al-Zn 1-0.2 Mn. mass fraction %), using Differential Calorimetric method. Through this method, the samples were heat treated up to 425° C, using different rates. To calculate the apparent activation energies associated with the formation of precipitated phases, we used different isoconversional methods. This study was supported by other analysis: X-ray diffraction and microhardness measurements.

Keywords: calorimetric, activation energy, AZ91 alloys, microstructural evolution

Procedia PDF Downloads 439
9319 Enhancing Greenhouse Productivity and Energy Efficiency Through UV-IR Reflective Coatings and Dust Mitigation: A Case Study in Saudi Arabia

Authors: Tayirjan Taylor Isimjan, Essam Jamea, Muien Qaryouti

Abstract:

The demand for efficient greenhouse production is escalating, necessitating continuous improvements in controlled plant growth environments. Central to maximizing growth are critical light-related factors, including quantity, quality, and geometric distribution of intercepted radiation. This becomes particularly crucial in regions like the Middle East, characterized by high solar radiation and dusty atmospheric conditions. Existing greenhouse technologies often rely on additional expensive equipment to manage light conditions effectively. In this study, we propose a distinct approach employing functional coatings to mitigate dust and block UV and IR radiation, thereby conserving energy and enhancing productivity. By combining UV-IR reflective coatings with dust mitigation strategies, we aim to address both environmental challenges and energy consumption issues faced by greenhouse agriculture in Saudi Arabia.

Keywords: greenhouse, UV-IR reflective coatings, dust mitigation, energy efficiency, productivity

Procedia PDF Downloads 58
9318 Wind Energy Harvester Based on Triboelectricity: Large-Scale Energy Nanogenerator

Authors: Aravind Ravichandran, Marc Ramuz, Sylvain Blayac

Abstract:

With the rapid development of wearable electronics and sensor networks, batteries cannot meet the sustainable energy requirement due to their limited lifetime, size and degradation. Ambient energies such as wind have been considered as an attractive energy source due to its copious, ubiquity, and feasibility in nature. With miniaturization leading to high-power and robustness, triboelectric nanogenerator (TENG) have been conceived as a promising technology by harvesting mechanical energy for powering small electronics. TENG integration in large-scale applications is still unexplored considering its attractive properties. In this work, a state of the art design TENG based on wind venturi system is demonstrated for use in any complex environment. When wind introduces into the air gap of the homemade TENG venturi system, a thin flexible polymer repeatedly contacts with and separates from electrodes. This device structure makes the TENG suitable for large scale harvesting without massive volume. Multiple stacking not only amplifies the output power but also enables multi-directional wind utilization. The system converts ambient mechanical energy to electricity with 400V peak voltage by charging of a 1000mF super capacitor super rapidly. Its future implementation in an array of applications aids in environment friendly clean energy production in large scale medium and the proposed design performs with an exhaustive material testing. The relation between the interfacial micro-and nano structures and the electrical performance enhancement is comparatively studied. Nanostructures are more beneficial for the effective contact area, but they are not suitable for the anti-adhesion property due to the smaller restoring force. Considering these issues, the nano-patterning is proposed for further enhancement of the effective contact area. By considering these merits of simple fabrication, outstanding performance, robust characteristic and low-cost technology, we believe that TENG can open up great opportunities not only for powering small electronics, but can contribute to large-scale energy harvesting through engineering design being complementary to solar energy in remote areas.

Keywords: triboelectric nanogenerator, wind energy, vortex design, large scale energy

Procedia PDF Downloads 213
9317 Challenges and Proposed Solutions Toward Successful Dealing with E-Waste in Kuwait

Authors: Salem Alajmi, Bader Altaweel

Abstract:

Kuwait, like many parts of the world, has started facing the dangerous growth of electrical and electronic wastes. This growth has been noted last two decades, coming along with the development of mobile phones, computers, TVs, as well as other electronic devices and electrical equipment. Kuwait is already among the highest global producers of electronic waste (E-waste) in kg per capita. Furthermore, Kuwait is among the global countries that set high-level future targets in renewable energy projects. Accumulation of this electronic waste, as well as accelerated renewable energy projects, will lead to the increase of future threats to the country. In this research, factors that lead to the increase the e-waste in Kuwait are presented. Also, the current situations of dealing with e-waste in the country as well as current challenges are examined. The impact of renewable energy projects on future E-wastes accumulation is considered. Moreover, this research proposes the best strategies and practices toward successfully dealing with the waste of electronic devices and renewable energy technologies.

Keywords: Kuwait, e-waste, extended producer responsibility, environment, recycle, recovery

Procedia PDF Downloads 180
9316 Simulation-Based Evaluation of Indoor Air Quality and Comfort Control in Non-Residential Buildings

Authors: Torsten Schwan, Rene Unger

Abstract:

Simulation of thermal and electrical building performance more and more becomes part of an integrative planning process. Increasing requirements on energy efficiency, the integration of volatile renewable energy, smart control and storage management often cause tremendous challenges for building engineers and architects. This mainly affects commercial or non-residential buildings. Their energy consumption characteristics significantly distinguish from residential ones. This work focuses on the many-objective optimization problem indoor air quality and comfort, especially in non-residential buildings. Based on a brief description of intermediate dependencies between different requirements on indoor air treatment it extends existing Modelica-based building physics models with additional system states to adequately represent indoor air conditions. Interfaces to corresponding HVAC (heating, ventilation, and air conditioning) system and control models enable closed-loop analyzes of occupants' requirements and energy efficiency as well as profitableness aspects. A complex application scenario of a nearly-zero-energy school building shows advantages of presented evaluation process for engineers and architects. This way, clear identification of air quality requirements in individual rooms together with realistic model-based description of occupants' behavior helps to optimize HVAC system already in early design stages. Building planning processes can be highly improved and accelerated by increasing integration of advanced simulation methods. Those methods mainly provide suitable answers on engineers' and architects' questions regarding more exuberant and complex variety of suitable energy supply solutions.

Keywords: indoor air quality, dynamic simulation, energy efficient control, non-residential buildings

Procedia PDF Downloads 231
9315 Power Generating Embedment beneath Vehicle Traffic Asphalt Roads

Authors: Ahmed Khalil

Abstract:

The discoveries in material sciences create an impulse in renewable energy transmission. Application techniques become more accessible by applied sciences. Variety of materials, application methods, and performance analyzing techniques can convert daily life functions to energy sources. These functions not only include natural sources like sun, wind, or water but also comprise the motion of tools used by human beings. In line with this, vehicles' motion, speed and weights come to the scene as energy sources together with piezoelectric nano-generators beneath the roads. Numerous application examples are put forward with repeated average performance, versus the differentiating challenges depending on geography and project conditions. Such holistic approach provides way for feed backs on research and improvement process of nano-generators beneath asphalt roads. This paper introduces the specific application methods of piezoelectric nano-generator beneath asphalt roads of Ahmadi Township in Kuwait.

Keywords: nano-generator pavements, piezoelectric, renewable energy, transducer

Procedia PDF Downloads 114
9314 Technical Sustainable Management: An Instrument to Increase Energy Efficiency in Wastewater Treatment Plants, a Case Study in Jordan

Authors: Dirk Winkler, Leon Koevener, Lamees AlHayary

Abstract:

This paper contributes to the improvement of the municipal wastewater systems in Jordan. An important goal is increased energy efficiency in wastewater treatment plants and therefore lower expenses due to reduced electricity consumption. The chosen way to achieve this goal is through the implementation of Technical Sustainable Management adapted to the Jordanian context. Three wastewater treatment plants in Jordan have been chosen as a case study for the investigation. These choices were supported by the fact that the three treatment plants are suitable for average performance and size. Beyond that, an energy assessment has been recently conducted in those facilities. The project succeeded in proving the following hypothesis: Energy efficiency in wastewater treatment plants can be improved by implementing principles of Technical Sustainable Management adapted to the Jordanian context. With this case study, a significant increase in energy efficiency can be achieved by optimization of operational performance, identifying and eliminating shortcomings and appropriate plant management. Implementing Technical Sustainable Management as a low-cost tool with a comparable little workload, provides several additional benefits supplementing increased energy efficiency, including compliance with all legal and technical requirements, process optimization, but also increased work safety and convenient working conditions. The research in the chosen field continues because there are indications for possible integration of the adapted tool into other regions and sectors. The concept of Technical Sustainable Management adapted to the Jordanian context could be extended to other wastewater treatment plants in all regions of Jordan but also into other sectors including water treatment, water distribution, wastewater network, desalination, or chemical industry.

Keywords: energy efficiency, quality management system, technical sustainable management, wastewater treatment

Procedia PDF Downloads 161
9313 Optimization of Wind Off-Grid System for Remote Area: Egyptian Application

Authors: Marwa M. Ibrahim

Abstract:

The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) off-grid system supplying a small remote gathering of four families using the HOMER software package. The second objective is to study the effect of wind energy system on the cost of generated electricity considering the cost of reducing CO₂ emissions as external benefit of wind turbines, no pollutant emission through the operational phase. The system consists of a small wind turbine, battery storage, and diesel generator. The electrical energy is to cater to the basic needs for which the daily load pattern is estimated at 8 kW peak. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for the selected site in Egypt. Using HOMER software, the simulation results shows that W/D/B systems are economical for the assumed community site as the price of generated electricity is about 0.285 $/kWh, without taking external benefits into considerations and 0.221 if CO₂ emissions taken into consideration W/D/B systems are more economical than alone diesel system as the COE is 0.432 $/kWh for diesel alone.

Keywords: renewable energy, hybrid energy system, on-off grid system, simulation, optimization and environmental impacts

Procedia PDF Downloads 101
9312 Energy Saving Potential with Improved Concrete in Ice Rink Floor Designs

Authors: Ehsan B. Haghighi, Pavel Makhnatch, Jörgen Rogstam

Abstract:

The ice rink floor is the largest heat exchanger in an ice rink. The important part of the floor consists of concrete, and the thermophysical properties of this concrete have strong influence on the energy usage of the ice rink. The thermal conductivity of concrete can be increased by using iron ore as ballast. In this study the Transient Plane Source (TPS) method showed an increase up to 58.2% of thermal conductivity comparing the improved concrete to standard concrete. Moreover, two alternative ice rink floor designs are suggested to incorporate the improved concrete. A 2D simulation was developed to investigate the temperature distribution in the conventional and the suggested designs. The results show that the suggested designs reduce the temperature difference between the ice surface and the brine by 1-4 ˚C, when comparing with convectional designs at equal heat flux. This primarily leads to an increased coefficient of performance (COP) in the primary refrigeration cycle and secondly to a decrease in the secondary refrigerant pumping power. The suggested designs have great potential to reduce the energy usage of ice rinks. Depending on the load scenario in the ice rink, the saving potential lies in the range of 3-10% of the refrigeration system energy usage. This calculation is based on steady state conditions and the potential with improved dynamic behavior is expected to increase the potential saving.

Keywords: Concrete, iron ore, ice rink, energy saving

Procedia PDF Downloads 340
9311 A Smartphone-Based Real-Time Activity Recognition and Fall Detection System

Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

Abstract:

Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

Procedia PDF Downloads 691
9310 V0 Physics at LHCb. RIVET Analysis Module for Z Boson Decay to Di-Electron

Authors: A. E. Dumitriu

Abstract:

The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

Procedia PDF Downloads 428
9309 The Combination Of Aortic Dissection Detection Risk Score (ADD-RS) With D-dimer As A Diagnostic Tool To Exclude The Diagnosis Of Acute Aortic Syndrome (AAS)

Authors: Mohamed Hamada Abdelkader Fayed

Abstract:

Background: To evaluate the diagnostic accuracy of (ADD-RS) with D-dimer as a screening test to exclude AAS. Methods: We conducted research for the studies examining the diagnostic accuracy of (ADD- RS)+ D-dimer to exclude the diagnosis of AAS, We searched MEDLINE, Embase, and Cochrane of Trials up to 31 December 2020. Results: We identified 3 studies using (ADD-RS) with D-dimer as a diagnostic tool for AAS, involving 3261 patients were AAS was diagnosed in 559(17.14%) patients. Overall results showed that the pooled sensitivities were 97.6 (95% CI 0.95.6, 99.6) at (ADD-RS)≤1(low risk group) with D-dimer and 97.4(95% CI 0.95.4,, 99.4) at (ADD-RS)>1(High risk group) with D-dimer., the failure rate was 0.48% at low risk group and 4.3% at high risk group respectively. Conclusions: (ADD-RS) with D-dimer was a useful screening test with high sensitivity to exclude Acute Aortic Syndrome.

Keywords: aortic dissection detection risk score, D-dimer, acute aortic syndrome, diagnostic accuracy

Procedia PDF Downloads 214
9308 Preparation of β-Polyvinylidene Fluoride Film for Self-Charging Lithium-Ion Battery

Authors: Nursultan Turdakyn, Alisher Medeubayev, Didar Meiramov, Zhibek Bekezhankyzy, Desmond Adair, Gulnur Kalimuldina

Abstract:

In recent years the development of sustainable energy sources is getting extensive research interest due to the ever-growing demand for energy. As an alternative energy source to power small electronic devices, ambient energy harvesting from vibration or human body motion is considered a potential candidate. Despite the enormous progress in the field of battery research in terms of safety, lifecycle and energy density in about three decades, it has not reached the level to conveniently power wearable electronic devices such as smartwatches, bands, hearing aids, etc. For this reason, the development of self-charging power units with excellent flexibility and integrated energy harvesting and storage is crucial. Self-powering is a key idea that makes it possible for the system to operate sustainably, which is now getting more acceptance in many fields in the area of sensor networks, the internet of things (IoT) and implantable in-vivo medical devices. For solving this energy harvesting issue, the self-powering nanogenerators (NGS) were proposed and proved their high effectiveness. Usually, sustainable power is delivered through energy harvesting and storage devices by connecting them to the power management circuit; as for energy storage, the Li-ion battery (LIB) is one of the most effective technologies. Through the movement of Li ions under the driving of an externally applied voltage source, the electrochemical reactions generate the anode and cathode, storing the electrical energy as the chemical energy. In this paper, we present a simultaneous process of converting the mechanical energy into chemical energy in a way that NG and LIB are combined as an all-in-one power system. The electrospinning method was used as an initial step for the development of such a system with a β-PVDF separator. The obtained film showed promising voltage output at different stress frequencies. X-ray diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) analysis showed a high percentage of β phase of PVDF polymer material. Moreover, it was found that the addition of 1 wt.% of BTO (Barium Titanate) results in higher quality fibers. When comparing pure PVDF solution with 20 wt.% content and the one with BTO added the latter was more viscous. Hence, the sample was electrospun uniformly without any beads. Lastly, to test the sensor application of such film, a particular testing device has been developed. With this device, the force of a finger tap can be applied at different frequencies so that electrical signal generation is validated.

Keywords: electrospinning, nanogenerators, piezoelectric PVDF, self-charging li-ion batteries

Procedia PDF Downloads 162
9307 Automated Detection of Women Dehumanization in English Text

Authors: Maha Wiss, Wael Khreich

Abstract:

Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

Procedia PDF Downloads 79
9306 Power Energy Management For A Grid-Connected PV System Using Rule-Base Fuzzy Logic

Authors: Nousheen Hashmi, Shoab Ahmad Khan

Abstract:

Active collaboration among the green energy sources and the load demand leads to serious issues related to power quality and stability. The growing number of green energy resources and Distributed-Generators need newer strategies to be incorporated for their operations to keep the power energy stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for energy power management in Grid-Connected Photovoltaic with energy storage system under set of constraints including weather conditions, Load Shedding Hours, Peak pricing Hours by using rule-based fuzzy smart grid controller to schedule power coming from multiple Power sources (photovoltaic, grid, battery) under the above set of constraints. The technique fuzzifies all the inputs and establishes fuzzify rule set from fuzzy outputs before defuzzification. Simulations are run for 24 hours period and rule base power scheduler is developed. The proposed fuzzy controller control strategy is able to sense the continuous fluctuations in Photovoltaic power generation, Load Demands, Grid (load Shedding patterns) and Battery State of Charge in order to make correct and quick decisions.The suggested Fuzzy Rule-based scheduler can operate well with vague inputs thus doesn’t not require any exact numerical model and can handle nonlinearity. This technique provides a framework for the extension to handle multiple special cases for optimized working of the system.

Keywords: photovoltaic, power, fuzzy logic, distributed generators, state of charge, load shedding, membership functions

Procedia PDF Downloads 478
9305 Integrated Waste-to-Energy Approach: An Overview

Authors: Tsietsi J. Pilusa, Tumisang G. Seodigeng

Abstract:

This study evaluates the benefits of advanced waste management practices in unlocking waste-to-energy opportunities within the solid waste industry. The key drivers of sustainable waste management practices, specifically with respect to packaging waste-to-energy technology options are discussed. The success of a waste-to-energy system depends significantly on the appropriateness of available technologies, including those that are well established as well as those that are less so. There are hard and soft interventions to be considered when packaging an integrated waste treatment solution. Technology compatibility with variation in feedstock (waste) quality and quantities remains a key factor. These factors influence the technology reliability in terms of production efficiencies and product consistency, which in turn, drives the supply and demand network. Waste treatment technologies rely on the waste material as feedstock; the feedstock varies in quality and quantities depending on several factors; hence, the technology fails, as a result. It is critical to design an advanced waste treatment technology in an integrated approach to minimize the possibility of technology failure due to unpredictable feedstock quality, quantities, conversion efficiencies, and inconsistent product yield or quality. An integrated waste-to-energy approach offers a secure system design that considers sustainable waste management practices.

Keywords: emerging markets, evaluation tool, interventions, waste treatment technologies

Procedia PDF Downloads 270
9304 Development of Dye Sensitized Solar Window by Physical Parameters Optimization

Authors: Tahsin Shameem, Chowdhury Sadman Jahan, Mohammad Alam

Abstract:

Interest about Net Zero Energy Buildings have gained traction in recent years following the need to sustain energy consumption with generations on site and to reduce dependence on grid supplied energy from large plants using fossil fuel. With this end in view, building integrated photovoltaics are being studied attempting to utilize all exterior facades of a building to generate power. In this paper, we have looked at the physical parameters defining a dye sensitized solar cell (DSSC) and discussed their impact on energy harvest. Following our discussion and experimental data obtained from literature, we have attempted to optimize these physical parameters accordingly so as to allow maximum light absorption for a given active layer thickness. We then modified a planer DSSC design with our optimized properties to allow adequate light transmission which demonstrated a high fill factor and an External Quantum Efficiency (EQE) of greater than 9% by computer aided design and simulation. In conclusion, a DSSC based solar window with such high output values even after such high light transmission through it definitely flags a promising future for this technology and our work elicits the need for further study and practical experimentation.

Keywords: net zero energy building, integrated photovoltaics, dye sensitized solar cell, fill factor, External Quantum Efficiency

Procedia PDF Downloads 140