Search results for: electrical machine

Authors: Elena C. Tamaş, Grațiela M. Țârlea, Gianni Flamaropol, Dragoș Hera

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This article is referring to a comparative study regarding the electrical energy consumption for lighting on diverse types of big sizes commercial buildings built in Romania after 2007, having 3, 4, 5 versus 8, 9, 10 operational years. Some buildings have installed building management systems (BMS) to monitor also the lighting performances starting with the opening days till the present days but some have chosen only local meters to implement. Firstly, for each analyzed building, the total required energy power and the energy power consumption for lighting were calculated depending on the lamps number, the unit power and the average daily running hours. All objects and installations were chosen depending on the destination/location of the lighting (exterior parking or access, interior or covering parking, building interior and building perimeter). Secondly, to all lighting objects and installations, mechanical counters were installed, and to the ones linked to BMS there were installed the digital meters as well for a better monitoring. Some efficient solutions are proposed to improve the power consumption, for example the 1/3 lighting functioning for the covered and exterior parking lighting to those buildings if can be done. This type of lighting share can be performed on each level, especially on the night shifts. Another example is to use the dimmers to reduce the light level, depending on the executed work in the respective area, and a 30% power energy saving can be achieved. Using the right BMS to monitor, the energy consumption depending on the average operational daily hours and changing the non-performant unit lights with the ones having LED technology or economical ones might increase significantly the energy performances and reduce the energy consumption of the buildings.

Keywords: commercial buildings, energy performances, lightning consumption, maintenance

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Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 379

Authors: Jan Dahlhaus, Alejandro Cardenas Miranda, Frederik Scholer, Maximilian Leonhardt, Matthias Moullion, Frank Beutenmuller, Julia Eckhardt, Josef Wasner, Frank Nittel, Sebastian Stoll, Devin Atukalp, Daniel Folgmann, Tobias Mayer, Obrad Dordevic, Paul Riley, Jean-Marc Le Peuvedic

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Electrical and hybrid aerospace technologies pose very challenging demands on the battery pack – especially with respect to weight and power. In the Clean Sky 2 research project LiBAT (funded by the EU), the consortium is currently building an ambitious prototype with state-of-the art cells that shows the potential of an intelligent pack design with a high level of integration, especially with respect to thermal management and power electronics. For the latter, innovative multi-level-inverter technology is used to realize the required power converting functions with reduced equipment. In this talk the key approaches and methods of the LiBat project will be presented and central results shown. Special focus will be set on the simulative methods used to support the early design and development stages from an overall system perspective. The applied methods can efficiently handle multiple domains and deal with different time and length scales, thus allowing the analysis and optimization of overall- or sub-system behavior. It will be shown how these simulations provide valuable information and insights for the efficient evaluation of concepts. As a result, the construction and iteration of hardware prototypes has been reduced and development cycles shortened.

Keywords: electric aircraft, battery, Li-ion, multi-level-inverter, Novec

Procedia PDF Downloads 151

Authors: Kougioumtzis Konstantin, Rylander Pär, Karlsteen Magnus

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Ball skills as a subset of fundamental motor skills are predictors for performance in sports. Currently, most tools evaluate ball skills utilizing subjective ratings. The aim of this study was to examine the psychometric properties of a newly developed instrument to objectively measure ball handling skills (BHS-test) utilizing digital instrument. Participants were a convenience sample of 213 adolescents (age M = 17.1 years, SD =3.6; 55% females, 45% males) recruited from upper secondary schools and invited to a sports hall for the assessment. The 8-item instrument incorporated both accuracy-based ball skill tests and repetitive-performance tests with a ball. Testers counted performance manually in the four tests (one throwing and three juggling tasks). Furthermore, assessment was technologically enhanced in the other four tests utilizing a ball machine, a Kinect camera and balls with motion sensors (one balancing and three rolling tasks). 3D printing technology was used to construct equipment, while all results were administered digitally with smart phones/tablets, computers and a specially constructed application to send data to a server. The instrument was deemed reliable (α = .77) and principal component analysis was used in a random subset (53 of the participants). Furthermore, latent variable modeling was employed to confirm the structure with the remaining subset (160 of the participants). The analysis showed good factorial-related validity with one factor explaining 57.90 % of the total variance. Four loadings were larger than .80, two more exceeded .76 and the other two were .65 and .49. The one factor solution was confirmed by a first order model with one general factor and an excellent fit between model and data (χ² = 16.12, DF = 20; RMSEA = .00, CI90 .00–.05; CFI = 1.00; SRMR = .02). The loadings on the general factor ranged between .65 and .83. Our findings indicate good reliability and construct validity for the BHS-test. To develop the instrument further, more studies are needed with various age-groups, e.g. children. We suggest using the BHS-test for diagnostic or assessment purpose for talent development and sports participation interventions that focus on ball games.

Keywords: ball-handling skills, ball-handling ability, technologically-enhanced measurements, assessment

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Authors: Mohamed Amhal, Jose Sayritupac

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Photovoltaic (PV) systems have risen as one of the modern renewable energy sources that are used in wide ranges to produce electricity and deliver it to the electrical grid. In parallel, monitoring systems have been deployed as a key element to track the energy production and to forecast the total production for the next days. The reliability of the PV energy production has become a crucial point in the analysis of PV systems. A deeper understanding of each phenomenon that causes a gain or a loss of energy is needed to better design, operate and maintain the PV systems. This work analyzes the current losses distribution in PV systems starting from the available solar energy, going through the DC side and AC side, to the delivery point. Most of the phenomena linked to energy losses and gains are considered and modeled, based on real time monitoring data and datasheets of the PV system components. An analysis of the order of magnitude of each loss is compared to the current literature and commercial software. To date, the analysis of PV systems performance based on a breakdown structure of energy losses and gains is not covered enough in the literature, except in some software where the concept is very common. The cutting-edge of the current analysis is the implementation of software tools for energy losses estimation in PV systems based on several energy losses definitions and estimation technics. The developed tools have been validated and tested on some PV plants in France, which are operating for years. Among the major findings of the current study: First, PV plants in France show very low rates of soiling and aging. Second, the distribution of other losses is comparable to the literature. Third, all losses reported are correlated to operational and environmental conditions. For future work, an extended analysis on further PV plants in France and abroad will be performed.

Keywords: energy gains, energy losses, losses distribution, monitoring, photovoltaic, photovoltaic systems

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Authors: Madikeri Rohit

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As energy efficiency is the key concern in many aircraft manufacturing companies regenerative braking is a technique using which energy lost due to friction while braking can be regained. In the operation of an aircraft, significant energy is lost during deceleration or braking which occurs during its landing phase. This problem can be overcome using Regenerative Breaking System (RBS) in landing gear. The major problem faced is regarding the batteries and the overall efficiency gained in competence with the added weight. As the amount of energy required to store is huge we need batteries with high capacity for storage. Another obstacle by using high capacity batteries is the added weight which undermines the efficiency obtained using RBS. An approach to this problem is to either use the obtained energy immediately without storage or to store in other forms such as mechanical, pneumatic and hydraulic. Problem faced with mechanical systems is the weight of the flywheel needed to obtain required efficiency. Pneumatic and hydraulic systems are a better option at present. Using hydraulic systems for storing energy is efficient as it integrates into the overall hydraulic system present in the aircraft. Another obstacle is faced with the redundancy of this system. Conventional braking must be used along with RBS in order to provide redundancy. Major benefits obtained using RBS is with the help of the energy obtained during landing which can be used of engine less taxing. This reduces fuel consumption as well as noise and air pollution. Another added benefit of using RBS is to provide electrical supply to lighting systems, cabin pressurization system and can be used for emergency power supply in case of electric failure. This paper discusses about using RBS in landing gear, problems, prospects and new techniques being pursued to improve RBS.

Keywords: regenerative braking, types of energy conversion, landing gear, energy storage

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: R. Hellmuth

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The orientation of flexibility and adaptability with regard to factory planning is at machine and process level. Factory buildings are not the focus of current research. Factory planning has the task of designing products, plants, processes, organization, areas and the construction of a factory. The adaptability of a factory can be divided into three types: spatial, organizational and technical adaptability. Spatial adaptability indicates the ability to expand and reduce the size of a factory. Here, the area-related breathing capacity plays the essential role. It mainly concerns the factory site, the plant layout and the production layout. The organizational ability to change enables the change and adaptation of organizational structures and processes. This includes structural and process organization as well as logistical processes and principles. New and reconfigurable operating resources, processes and factory buildings are referred to as technical adaptability. These three types of adaptability can be regarded independently of each other as undirected potentials of different characteristics. If there is a need for change, the types of changeability in the change process are combined to form a directed, complementary variable that makes change possible. When planning adaptability, importance must be attached to a balance between the types of adaptability. The vision of the intelligent factory building and the 'Internet of Things' presupposes the comprehensive digitalization of the spatial and technical environment. Through connectivity, the factory building must be empowered to support a company's value creation process by providing media such as light, electricity, heat, refrigeration, etc. In the future, communication with the surrounding factory building will take place on a digital or automated basis. In the area of industry 4.0, the function of the building envelope belongs to secondary or even tertiary processes, but these processes must also be included in the communication cycle. An integrative view of a continuous communication of primary, secondary and tertiary processes is currently not yet available and is being developed with the aid of methods in this research work. A comparison of the digital twin from the point of view of production and the factory building will be developed. Subsequently, a tool will be elaborated to classify digital twins from the perspective of data, degree of visualization, and the trades. Thus a contribution is made to better integrate the secondary and tertiary processes in a factory into the added value.

Keywords: adaptability, digital factory twin, factory planning, industry 4.0

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Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Today, with the increase in quantity and quality and variety of crimes, the discussion of crime prevention has faced a serious challenge that human resources alone and with traditional methods will not be effective. One of the developments in the modern world is the presence of artificial intelligence in various fields, including criminal law. In fact, the use of artificial intelligence in criminal investigations and fighting crime is a necessity in today's world. The use of artificial intelligence is far beyond and even separate from other technologies in the struggle against crime. Second, its application in criminal science is different from the discussion of prevention and it comes to the prediction of crime. Crime prevention in terms of the three factors of the offender, the offender and the victim, following a change in the conditions of the three factors, based on the perception of the criminal being wise, and therefore increasing the cost and risk of crime for him in order to desist from delinquency or to make the victim aware of self-care and possibility of exposing him to danger or making it difficult to commit crimes. While the presence of artificial intelligence in the field of combating crime and social damage and dangers, like an all-seeing eye, regardless of time and place, it sees the future and predicts the occurrence of a possible crime, thus prevent the occurrence of crimes. The purpose of this article is to collect and analyze the studies conducted on the use of artificial intelligence in predicting and preventing crime. How capable is this technology in predicting crime and preventing it? The results have shown that the artificial intelligence technologies in use are capable of predicting and preventing crime and can find patterns in the data set. find large ones in a much more efficient way than humans. In crime prediction and prevention, the term artificial intelligence can be used to refer to the increasing use of technologies that apply algorithms to large sets of data to assist or replace police. The use of artificial intelligence in our debate is in predicting and preventing crime, including predicting the time and place of future criminal activities, effective identification of patterns and accurate prediction of future behavior through data mining, machine learning and deep learning, and data analysis, and also the use of neural networks. Because the knowledge of criminologists can provide insight into risk factors for criminal behavior, among other issues, computer scientists can match this knowledge with the datasets that artificial intelligence uses to inform them.

Keywords: artificial intelligence, criminology, crime, prevention, prediction

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Authors: Dhouibi Mohamed, Stirbu Bogdan, Chabotier André, Pirlot Marc

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Effects of erosion and wear on the performance of small caliber guns have been analyzed throughout numerical and experimental studies. Mainly, qualitative observations were performed. Correlations between the volume change of the chamber and the maximum pressure are limited. This paper focuses on the development of a numerical model to predict the maximum pressure evolution when the interior shape of the chamber changes in the different weapon’s life phases. To fulfill this goal, an experimental campaign, followed by a numerical simulation study, is carried out. Two test barrels, « 5.56x45mm NATO » and « 7.62x51mm NATO,» are considered. First, a Coordinate Measuring Machine (CMM) with a contact scanning probe is used to measure the interior profile of the barrels after each 300-shots cycle until their worn out. Simultaneously, the EPVAT (Electronic Pressure Velocity and Action Time) method with a special WEIBEL radar are used to measure: (i) the chamber pressure, (ii) the action time, (iii) and the bullet velocity in each barrel. Second, a numerical simulation study is carried out. Thus, a coupled interior ballistic model is developed using the dynamic finite element program LS-DYNA. In this work, two different models are elaborated: (i) coupled Eularien Lagrangian method using fluid-structure interaction (FSI) techniques and a coupled thermo-mechanical finite element using a lumped parameter model (LPM) as a subroutine. Those numerical models are validated and checked through three experimental results, such as (i) the muzzle velocity, (ii) the chamber pressure, and (iii) the surface morphology of fired projectiles. Results show a good agreement between experiments and numerical simulations. Next, a comparison between the two models is conducted. The projectile motions, the dynamic engraving resistances and the maximum pressures are compared and analyzed. Finally, using this obtained database, a statistical correlation between the muzzle velocity, the maximum pressure and the chamber volume is established.

Keywords: engraving process, finite element analysis, gun barrel erosion, interior ballistics, statistical correlation

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Authors: Băilă Diana Irinel, Păcurar Răzvan, Păcurar Ancuța

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Although the volumes of fibre reinforced polymer composites (FRPs) used for aircraft applications is a relatively small percentage of total use, the materials often find their most sophisticated applications in this industry. In aerospace, the performance criteria placed upon materials can be far greater than in other areas – key aspects are light-weight, high-strength, high-stiffness, and good fatigue resistance. Composites were first used by the military before the technology was applied to commercial planes. Nowadays, composites are widely used, and this has been the result of a gradual direct substitution of metal components followed by the development of integrated composite designs as confidence in FRPs has increased. The airplane uses a range of components made from composites, including the fin and tailplane. In the last years, composite materials are increasingly used in automotive applications due to the improvement of material properties. In the aerospace and automotive sector, the fuel consumption is proportional to the weight of the body of the vehicle. A minimum of 20% of the cost can be saved if it used polymer composites in place of the metal structures and the operating and maintenance costs are alco very low. Glass fiber-epoxy composites are widely used in the making of aircraft and automobile body parts and are not only limited to these fields but also used in ship building, structural applications in civil engineering, pipes for the transport of liquids, electrical insulators in reactors. This article was establish the high-performance of composite material, a type glass-epoxy used in automotive and aeronautic domains, concerning the tensile and flexural tests and SEM analyzes.

Keywords: glass-epoxy composite, traction and flexion tests, SEM analysis, acoustic emission (AE) signals

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Authors: Ibrahim Sengor, Sumeyye Cesur, Ilyas Kartal, Faik Nuzhet Oktar, Nazmi Ekren, Ahmet Talat Inan, Oguzhan Gunduz

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In recent years, many researchers focused on nano-size fiber production. Nanofibers have been studied due to their different and superior physical, chemical and mechanical properties. Poly (lactic acid) (PLA), is a type of biodegradable thermoplastic polyester derived from renewable sources used in biomedical owing to its biocompatibility and biodegradability. In addition, zinc oxide is an antibacterial material and hazelnut shell powder is a filling material. In this study, nanofibers were obtained by adding of different ratio Zinc oxide, (ZnO) and hazelnut shell powder at different concentration into Poly (lactic acid) (PLA) by using electrospinning method which is the most common method to obtain nanofibers. After dissolving the granulated polylactic acids in % 1,% 2,% 3 and% 4 with chloroform solvent, they are homogenized by adding tween and hazelnut shell powder at different ratios and then by electrospinning, nanofibers are obtained. Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), Differential scanning calorimeter (DSC) and physical analysis such as density, electrical conductivity, surface tension, viscosity measurement and antimicrobial test were carried out after production process. The resulting structures of the nanofiber possess antimicrobial and antiseptic properties, which are attractive for biomedical applications. The resulting structures of the nanofiber possess antimicrobial, non toxic, self-cleaning and rigid properties, which are attractive for biomedical applications.

Keywords: electrospinning, hazelnut shell powder, nanofibers, poly (lactic acid), zinc oxide

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Authors: Bharath Anantharamaiah, Tomas Bouda, Elke Deckers, Stijn Jonckheere, Wim Desmet, Juan J. Garcia

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Automotive tyres are gaining importance recently in terms of their noise emission, not only with respect to reduction in noise, but also their perception and detection. Tyres exhibit a mechanical noise generation mechanism up to 1 kHz. However, owing to the fact that tyre is a composite of several materials, it has been difficult to model it using finite elements to predict noise at high frequencies. The currently available FE models have a reliability of about 500 Hz, the limit which, however, is not enough to perceive the roughness or sharpness of noise from tyre. These noise components are important in order to alert pedestrians on the street about passing by slow, especially electric vehicles. In order to model tyre noise behaviour up to 1 kHz, its dynamic behaviour must be accurately developed up to a 1 kHz limit using finite elements. Materials play a vital role in modelling the dynamic tyre behaviour precisely. Since tyre is a composition of several components, their precise definition in finite element simulations is necessary. However, during the tyre manufacturing process, these components are subjected to various pressures and temperatures, due to which these properties could change. Hence, material definitions are better described based on the tyre responses. In this work, the hyperelasticity of tyre component rubbers is calibrated, using the design of experiments technique from the tyre characteristic responses that are measured on a stiffness measurement machine. The viscoelasticity of rubbers are defined by the Prony series for rubbers, which are determined from the loss factor relationship between the loss and storage moduli, assuming that the rubbers are excited within the linear viscoelasticity ranges. These values of loss factor are measured and theoretically expressed as a function of rubber shore hardness or hyperelasticities. From the results of the work, there exists a good correlation between test and simulation vibrational transfer function up to 1 kHz. The model also allows flexibility, i.e., the frequency limit can also be extended, if required, by calibrating the Prony parameters of rubbers corresponding to the frequency of interest. As future work, these tyre models are used for noise generation at high frequencies and thus for tyre noise perception.

Keywords: tyre dynamics, rubber materials, prony series, hyperelasticity

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Lazhar Belkhiri, Ammar Tiri, Lotfi Mouni

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In this research, we analyzed the groundwater quality index in the El Milia plain, Kebir Rhumel Basin, Algeria. Thirty-three groundwater samples were collected from wells in the El Milia plain during April 2015. In this study, pH and electrical conductivity (EC) were conducted at each sampling well. Eight hydrochemical parameters such as calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), chlorid (Cl), sulfate (SO4), bicarbonate (HCO3), and Nnitrate (NO3) were analysed. The entropy water quality index (EWQI) method was employed to evaluate the groundwater quality in the study area. Moran’s I and the ordinary kriging (OK) interpolation technique were used to examine the spatial distribution pattern of the hydrochemical parameters in the groundwater. It was found that the hydrochemical parameters Ca, Cl, and HCO3 showed strong spatial autocorrelation in the El Milia plain, indicating a spatial dependence and clustering of these parameters in the groundwater. The groundwater quality was evaluated using the entropy water quality index (EWQI). The results showed that approximately 86% of the total groundwater samples in the study area fall within the moderate groundwater quality category. The spatial map of the EWQI values indicated an increasing trend from the south-west to the northeast, following the direction of groundwater flow. The highest EWQI values were observed near El Milia city in the center of the plain. This spatial pattern suggests variations in groundwater quality across the study area, with potentially higher risks near the city center. Therefore, the results obtained in this research provide very useful information to decision-makers.

Keywords: entropy water quality index (EWQI), moran’s i, ordinary kriging interpolation, el milia plain

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Authors: Timine Suoware, Sylvester Edelugo, Charles Amgbari

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The susceptibility of natural fibre polymer composites to flame has necessitated research to improve and develop flame retardant (FR) to delay the escape of combustible volatiles. Previous approaches relied mostly on FR such as aluminium tri-hydroxide (ATH) and ammonium polyphosphate (APP) to improve fire performances of wood sawdust polymer composites (WSPC) with emphasis on non-structural building applications. In this paper, APP was modified with gum Arabic powder (GAP) and then hybridized with ATH at 0, 12 and 18% loading ratio to form new FR species; WSPC12%APP-GAP and WSPC18%ATH/APP-GAP. The FR species were incorporated in wood sawdust waste reinforced in polyester resin to form panels for fireproof doors. The panels were produced using hand lay compression moulding technique and cured at room temperature. Specimen cut from panels were then tested for tensile strength (TS), flexural strength (FS) and impact strength (IS) using universal testing machine and impact tester; thermal stability using (TGA/DSC 1: Metler Toledo); time-to-ignition (Tig), heat release rates (HRR); peak HRR (HRRp), average HRR (HRRavg), total HRR (THR), peak mass loss rate (MLRp), average smoke production rate (SPRavg) and carbon monoxide production (COP ) were obtained using the cone calorimeter apparatus. From the mechanical properties obtained, improvements of IS for the panels were not noticeable whereas TS and FS for WSPC12%APP-GAP respectively stood at 12.44 MPa and 85.58 MPa more than those without FR (WSPC0%). For WSC18%ATH/APP-GAP TS and FS respectively stood at 16.45 MPa and 50.49 MPa more compared to (WSPC0%). From the thermal analysis, the panels did not exhibit any significant change as early degradation was observed. At 900 OC, the char residues improved by 15% for WSPC12%APP-GAP and 19% for WSPC18%ATH/APP-GAP more than (WSC0%) at 5%, confirming the APP-GAP to be a good FR. At 50 kW/m2 heat flux (HF), WSPC12%APP-GAP improved better the fire behaviour of the panels when compared to WSC0% as follows; Tig = 46 s, HRRp = 56.1 kW/2, HRRavg = 32.8 kW/m2, THR = 66.6 MJ/m2, MLRp = 0.103 g/s, TSR = 0.04 m2/s and COP = 0.051 kg/kg. These were respectively more than WSC0%. It can be concluded that the new concept of modifying FR with GAP in WSC could meet the requirement of a fireproof door for building applications.

Keywords: composite, flame retardant, wood sawdust, fireproof doors

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Authors: Aphinan Phukaoluan, Surachai Dechkunakorn, Niwat Anuwongnukroh, Anak Khantachawana, Pongpan Kaewtathip, Julathep Kajornchaiyakul, Peerapong Tua-Ngam

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Aims: The objectives of this study was to determine the load-deflecting characteristics of a fabricated orthodontic wire with alloy composition of 50.6% (atomic weight) Ni and 49.4% (atomic weight) Ti and to compare the results with Ormco, a commercially available pre-formed NiTi orthodontic archwire. Materials and Methods: The ingots alloys with atomic weight ratio 50.6 Ni: 49.4 Ti alloy were used in this study. Three specimens were cut to have wire dimensions of 0.016 inch x0.022 inch. For comparison, a commercially available pre-formed NiTi archwire, Ormco, with dimensions of 0.016 inch x 0.022 inch was used. Three-point bending tests were performed at the temperature 36+1 °C using a Universal Testing Machine on the newly fabricated and commercial archwires to assess the characteristics of the load-deflection curve with loading and unloading forces. The loading and unloading features at the deflection points 0.25, 0.50, 0.75. 1.0, 1.25, and 1.5 mm were compared. Descriptive statistics was used to evaluate each variables, and independent t-test at p < 0.05 was used to analyze the mean differences between the two groups. Results: The load-deflection curve of the 50.6Ni: 49.4Ti wires exhibited the characteristic features of superelasticity. The curves at the loading and unloading slope of Ormco NiTi archwire were more parallel than the newly fabricated NiTi wires. The average deflection force of the 50.6Ni: 49.4Ti wire was 304.98 g and 208.08 g for loading and unloading, respectively. Similarly, the values were 358.02 g loading and 253.98 g for unloading of Ormco NiTi archwire. The interval difference forces between each deflection points were in the range 20.40-121.38 g and 36.72-92.82 g for the loading and unloading curve of 50.6Ni: 49.4Ti wire, respectively, and 4.08-157.08 g and 14.28-90.78 g for the loading and unloading curve of commercial wire, respectively. The average deflection force of the 50.6Ni: 49.4Ti wire was less than that of Ormco NiTi archwire, which could have been due to variations in the wire dimensions. Although a greater force was required for each deflection point of loading and unloading for the 50.6Ni: 49.4Ti wire as compared to Ormco NiTi archwire, the values were still within the acceptable limits to be clinically used in orthodontic treatment. Conclusion: The 50.6Ni: 49.4Ti wires presented the characteristics of a superelastic orthodontic wire. The loading and unloading force were also suitable for orthodontic tooth movement. These results serve as a suitable foundation for further studies in the development of new orthodontic NiTi archwires.

Keywords: 50.6 ni 49.4 Ti alloy wire, load deflection curve, loading and unloading force, orthodontic

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

Procedia PDF Downloads 38

Authors: Uday Shanker Goel, Vinay Vasant Mahashabde, Biswajit Ghosh, Arvind Jha, Amit Kumar, Sanjay Kumar Patel, Uma Shanker Pattanaik, Vinit Kumar Shah, Chaitanya Bhanu

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Pinch rolls of the Hot Mills must possess resistance to wear, thermal stability, high thermal conductivity and through hardness. Conventionally, pinch rolls have been procured either as new ones or refurbished ones. Discarded Work Rolls from the Cold Mill were taken and machined inhouse at Tata Steel to be used subsequently as the bottom pinch rolls of the Hot Mill. The hardness of the scrapped work rolls from CRM is close to 55HRC and the typical composition is ( C - 0.8% , Mn - 0.40 % , Si - 0.40% , Cr - 3.5% , Mo - 0.5% & V - 0.1% ).The Innovation was the use of a roll which would otherwise have been otherwise discarded as scrap. Also, the innovation helped in using the scrapped roll which had better wear and heat resistance. In a conventional Pinch roil (Hardness 50 HRC and typical chemistry - C - 10% , Mo+Co+V+Nb ~ 5 % ) , Pick-up is a condition whereby foreign material becomes adhered to the surface of the pinch roll during service. The foreign material is usually adhered metal from the actual product being rolled. The main attributes of the weld overlay rolls are wear resistance and crack resistance. However, the weld overlay roll has a strong tendency for strip pick-up particularly in the area of bead overlap. However, the greatest disadvantage is the depth of weld deposit, which is less than half of the usable shell thickness in most mills. Because of this, the stainless rolls require re-welding on a routine basis. By providing a significantly cheaper in house and more robust alternative of the existing bottom pinch rolls , this innovation results in significant lower worries for the roll shop. Pinch rolls now don't have to be sent outside Jamshedpur for refurbishment or for procuring new ones. Scrapped rolls from adjacent Cold Mill are procured and sent for machining to our Machine Shop inside Tata Steel works in Jamshedpur. This is far more convenient than the older methodology. The idea is also being deployed to the other hot mills of Tata Steel. Multiple campaigns have been tried out at both down coilers of Hot Strip with significantly lower wear.

Keywords: hot rolling flat, cold mill work roll, hot strip pinch roll, strip surface

Procedia PDF Downloads 112

Authors: M. A. Mamun, M. I. Khan, M. H. Sarker, K. A. Khan, M. Shajahan

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The study was carried out to investigate on an innovative invention, Pathor Kuchi Leaf (PKL) cell, which is fueled with PKL sap of widely available plant called Bryophyllum pinnatum as an energy source for use in PKL battery to generate electricity. This battery, a primary source of electricity, has several order of magnitude longer shelf-lives than the traditional Galvanic cell battery, is still under investigation. In this regard, we have conducted some experiments using various instruments including Atomic Absorption Spectrophotometer (AAS), Ultra-Violet Visible spectrophotometer (UV-Vis), pH meter, Ampere-Volt-Ohm Meter (AVO Meter), etc. The AAS, UV-Vis, and pH-metric analysis data provided that the potential and current were produced as the Zn electrode itself acts as reductant while Cu2+ and H+ ions are behaving as the oxidant. The significant influence of secondary salt on current and potential leads to the dissociation of weak organic acids in PKL juice, and subsequent enrichment to the reactant ions by the secondary salt effects. However, the liquid junction potential was not as great as minimized with the opposite transference of organic acid anions and H+ ions as their dissimilar ionic mobilities. Moreover, the large value of the equilibrium constant (K) implies the big change in Gibbs free energy (∆G), the more electromotive force works in electron transfer during the forward electrochemical reaction which coincides with the fast reduction of the weight of zinc plate, revealed the additional electrical work in the presence of PKL sap. This easily fabricated high-performance PKL battery can show an excellent promise during the off-peak across the countryside.

Keywords: Atomic Absorption Spectrophotometer (AAS), Bryophylum Pinnatum Leaf (BPL), electricity, electrochemistry, organic acids

Procedia PDF Downloads 313

Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

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The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

Procedia PDF Downloads 98

Authors: Samhita Mummadi, Sree Divya Nagalli, Harshini Vemuri, Saketh Charan Nakka, Sumesh K. J.

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One of the most significant challenges faced by people in today’s digital era is an alarming increase in fraudulent activities on online platforms. The fascination with online shopping to avoid long queues in shopping malls, the availability of a variety of products, and home delivery of goods have paved the way for a rapid increase in vast online shopping platforms. This has had a major impact on increasing fraudulent activities as well. This loop of online shopping and transactions has paved the way for fraudulent users to commit fraud. For instance, consider a store that orders thousands of products all at once, but what’s fishy about this is the massive number of items purchased and their transactions turning out to be fraud, leading to a huge loss for the seller. Considering scenarios like these underscores the urgent need to introduce machine learning approaches to combat fraud in online shopping. By leveraging robust algorithms, namely KNN, Decision Trees, and Random Forest, which are highly effective in generating accurate results, this research endeavors to discern patterns indicative of fraudulent behavior within transactional data. Introducing a comprehensive solution to this problem in order to empower e-commerce administrators in timely fraud detection and prevention is the primary motive and the main focus. In addition to that, sentiment analysis is harnessed in the model so that the e-commerce admin can tailor to the customer’s and consumer’s concerns, feedback, and comments, allowing the admin to improve the user’s experience. The ultimate objective of this study is to ramp up online shopping platforms against fraud and ensure a safer shopping experience. This paper underscores a model accuracy of 84%. All the findings and observations that were noted during our work lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as technologies continue to evolve.

Keywords: behavior analysis, feature selection, Fraudulent pattern recognition, imbalanced classification, transactional anomalies

Procedia PDF Downloads 7

Authors: Raviteja Chintala

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Water shortage in many areas of the world have predominantly increased the demand for efficient methods involved in the production of drinking water, So purification of water invoking cost effective and efficient methods is a challenging field of research. In this regard, Reverse osmosis membrane desalination of both seawater and inland brackish water is currently being deployed in various locations around the world. In the present work an attempt is made to integrate these existing technologies with novel method, Wherein carbon nanotubes at the lab scale are prepared which further replace activated carbon tubes being used traditionally. This has proven to enhance the efficiency of the water filter, Effectively neutralising most of the organic impurities. Furthermore, This ensures the reduction in TDS. Carbon nanotubes have wide range in scope of applications such as composite reinforcements, Field emitters, Sensors, Energy storage and energy conversion devices and catalysts support phases, Because of their unusual mechanical, Electrical, Thermal and structural properties. In particular, The large specific surface area, as well as the high chemical and thermal stability, Makes carbon nanotube an attractive adsorbent in waste water treatment. Carbon nanotubes are effective in eliminating these harmful media from water as an adsorbent. In this work, Candle soot method has been incorporated for the preparation of carbon nanotubes and mixed with activated charcoal in different compositions. The effect of composition change is monitored by using TDS measuring meter. As the composition of Nano carbon increases, The TDS of the water gradually decreases. In order to enhance the life time for carbon filter, Nano tubes are provided with larger surface area.

Keywords: TDS (Total Dissolved Solids), carbon nanotubes, water, candle soot

Procedia PDF Downloads 324

Authors: Wiqar Hussain Shah

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The Structural, magnetic and transport behavior of La1-xCaxMnO3+ (x=0.48, 0.50, 0.52 and 0.55 and =0.015) compositions close to charge ordering, was studied through XRD, resistivity, DC magnetization and AC susceptibility measurements. With time and thermal cycling (T<300 K) there is an irreversible transformation of the low-temperature phase from a partially ferromagnetic and metallic to one that is less ferromagnetic and highly resistive. For instance, an increase of resistivity can be observed by thermal cycling, where no effect is obtained for lower Ca concentration. The time changes in the magnetization are logarithmic in general and activation energies are consistent with those expected for electron transfer between Mn ions. The data suggest that oxygen non-stoichiometry results in mechanical strains in this two-phase system, leading to the development of irreversible metastable states, which relax towards the more stable charge-ordered and antiferromagnetic microdomains at the nano-meter size. This behavior is interpreted in terms of strains induced charge localization at the interface between FM/AFM domains in the antiferromagnetic matrix. Charge, orbital ordering and phase separation play a prominent role in the appearance of such properties, since they can be modified in a spectacular manner by external factor, making the different physical properties metastable. Here we describe two factors that deeply modify those properties, viz. the doping concentration and the thermal cycling. The metastable state is recovered by the high temperature annealing. We also measure the magnetic relaxation in the metastable state and also the revival of the metastable state (in a relaxed sample) due to high temperature (800 ) thermal treatment.

Keywords: Rare-earth maganites, nano-structural materials, doping effects on electrical, magnetic properties, competing interactions

Procedia PDF Downloads 115

Authors: Mohammad M. Khan, Gajendra Dixit

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Partially lubricated sliding wear behaviour of a zinc-based alloy reinforced with 10wt% SiC particles has been studied as a function of applied load and solid lubricant particle size and has been compared with that of matrix alloy and conventionally used grey cast iron. The wear tests were conducted at the sliding velocities of 2.1m/sec in various partial lubricated conditions using pin on disc machine as per ASTM G-99-05. Base oil (SAE 20W-40) or mixture of the base oil with 5wt% graphite of particle sizes (7-10 µm) and (100 µm) were used for creating lubricated conditions. The matrix alloy revealed primary dendrites of a and eutectoid a + h and Î phases in the Inter dendritic regions. Similar microstructure has been depicted by the composite with an additional presence of the dispersoid SiC particles. In the case of cast iron, flakes of graphite were observed in the matrix; the latter comprised of (majority of) pearlite and (limited quantity of) ferrite. Results show a large improvement in wear resistance of the zinc-based alloy after reinforcement with SiC particles. The cast iron shows intermediate response between the matrix alloy and composite. The solid lubrication improved the wear resistance and friction behaviour of both the reinforced and base alloy. Moreover, minimum wear rate is obtained in oil+ 5wt % graphite (7-10 µm) lubricated environment for the matrix alloy and composite while for cast iron addition of solid lubricant increases the wear rate and minimum wear rate is obtained in case of oil lubricated environment. The cast iron experienced higher frictional heating than the matrix alloy and composite in all the cases especially at higher load condition. As far as friction coefficient is concerned, a mixed trend of behaviour was noted. The wear rate and frictional heating increased with load while friction coefficient was affected in an opposite manner. Test duration influenced the frictional heating and friction coefficient of the samples in a mixed manner.

Keywords: solid lubricant, sliding wear, grey cast iron, zinc based metal matrix composites

Procedia PDF Downloads 301

Authors: Mikhail O. Eremin

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Present work is devoted to experimental study and numerical modelling of failure of rocks typical for Kuzbass coal basin (Russia). The main goal was to define strength and deformation characteristics of rocks on the base of uniaxial compression and three-point bending loadings and then to build a mathematical model of failure process for both types of loading. Depending on particular physical-mechanical characteristics typical rocks of Kuzbass coal basin (sandstones, siltstones, mudstones, etc. of different series – Kolchuginsk, Tarbagansk, Balohonsk) manifest brittle and quasi-brittle character of failure. The strength characteristics for both tension and compression are found. Other characteristics are also found from the experiment or taken from literature reviews. On the base of obtained characteristics and structure (obtained from microscopy) the mathematical and structural models are built and numerical modelling of failure under different types of loading is carried out. Effective characteristics obtained from modelling and character of failure correspond to experiment and thus, the mathematical model was verified. An Instron 1185 machine was used to carry out the experiments. Mathematical model includes fundamental conservation laws of solid mechanics – mass, impulse, energy. Each rock has a sufficiently anisotropic structure, however, each crystallite might be considered as isotropic and then a whole rock model has a quasi-isotropic structure. This idea gives an opportunity to use the Hooke’s law inside of each crystallite and thus explicitly accounting for the anisotropy of rocks and the stress-strain state at loading. Inelastic behavior is described in frameworks of two different models: von Mises yield criterion and modified Drucker-Prager yield criterion. The damage accumulation theory is also implemented in order to describe a failure process. Obtained effective characteristics of rocks are used then for modelling of rock mass evolution when mining is carried out both by an open-pit or underground opening.

Keywords: damage accumulation, Drucker-Prager yield criterion, failure, mathematical modelling, three-point bending, uniaxial compression

Procedia PDF Downloads 159

Authors: Prima Fithri, Lusi Susanti, Karin Bestarina

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Indonesia's electrification ratio is still around 80.1%, which means that approximately 19.9% of households in Indonesia have not been getting the flow of electrical energy. Household electricity consumptions in Indonesia are generally still dominated by the public urban. In the city of Padang, West Sumatera, Indonesia, about 94.10% are power users of government services (PLN). The most important thing of the issue is human resources efficient energy. Consumer behavior in utilizing electricity becomes significant. Intensive questioner survey, in-depth interview and statistical analysis are carried out to collect scientific evidences of the behavioral based changes instruments to reduce electricity consumption in household sector. The questioner was developed to include five factors assuming affect the electricity consumption pattern in household sector. They are: attitude, energy price, household income, knowledge and other determinants. The survey was carried out in Padang, West Sumatra Province Indonesia. About 210 questioner papers were proportionally distributed to households in 11 districts in Padang. Stratified sampling was used as a method to select respondents. The results show that the household size, income, payment methods and size of house are factors affecting electricity saving behavior in residential sector. Household expenses on electricity are strongly influenced by gender, type of job, level of education, size of house, income, payment method and level of installed power. These results provide a scientific evidence for stakeholders on the potential of controlling electricity consumption and designing energy policy by government in residential sector.

Keywords: electricity, energy saving, household, behavior, policy

Procedia PDF Downloads 514

Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

Procedia PDF Downloads 146

Authors: Nedal N. Marei, Nashaat Nassar

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Many treatment techniques have been used to remove the soluble pollutants from wastewater as; dyes and metal ions which could be found in rich amount in the used water of the textile and tanneries industry. The effluents from these industries are complex, containing a wide variety of dyes and other contaminants, such as dispersants, acids, bases, salts, detergents, humectants, oxidants, and others. These techniques can be divided into physical, chemical, and biological methods. Adsorption has been developed as an efficient method for the removal of heavy metals from contaminated water and soil. It is now recognized as an effective method for the removal of both organic and inorganic pollutants from wastewaters. Nanosize materials are new functional materials, which offer high surface area and have come up as effective adsorbents. Nano alumina is one of the most important ceramic materials widely used as an electrical insulator, presenting exceptionally high resistance to chemical agents, as well as giving excellent performance as a catalyst for many chemical reactions, in microelectronic, membrane applications, and water and wastewater treatment. In this study, methylene blue (MB) dye has been used as model dye of textile wastewater in order to synthesize a synthetic MB wastewater. NiO nanoparticles were added in small percentage in the sand packed bed adsorption columns to remove the MB from the synthetic textile wastewater. Moreover, different parameters have been evaluated; flow of the synthetic wastewater, pH, height of the bed, percentage of the NiO to the sand in the packed material. Different mathematical models where employed to find the proper model which describe the experimental data and help to analyze the mechanism of the MB adsorption. This study will provide good understanding of the dyes adsorption using metal oxide nanoparticles in the classical sand bed.

Keywords: adsorption, column, nanoparticles, methylene

Procedia PDF Downloads 249

Authors: Romeo Malik, Yashraj Tripathy, Anup Barai

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Transportation safety is a major concern for vehicle electrification on a large-scale. The failure cost of lithium-ion batteries is substantial and is significantly impacted by higher liability and replacement cost. With continuous advancement on the material front in terms of higher energy density, upgrading safety characteristics are becoming more crucial for broader integration of lithium-ion batteries. Understanding and impeding thermal runaway is the prime issue for battery safety researchers. In this study, a comprehensive comparison of thermal runaway mechanisms for two different cathode types, Li(Ni₀.₃Co₀.₃Mn₀.₃)O₂ and Li(Ni₀.₈Co₀.₁₅Al₀.₀₅)O₂ is explored. Both the chemistries were studied for different states of charge, and the various abuse scenarios that lead to thermal runaway is investigated. Abuse tests include mechanical abuse, electrical abuse, and thermal abuse. Batteries undergo thermal runaway due to a series of combustible reactions taking place internally; this is observed as multiple jets of flame reaching temperatures of the order of 1000ºC. The physicochemical characterisation was performed on cells, prior to and after abuse. Battery’s state of charge and chemistry have a significant effect on the flame temperature profiles which is otherwise quantified as heat released. Majority of the failures during transportation is due to these external short circuit. Finally, a mitigation approach is proposed to impede the thermal runaway hazard. Transporting lithium-ion batteries under low states of charge is proposed as a way forward. Batteries at low states of charge have demonstrated minimal heat release under thermal runaway reducing the risk of secondary hazards such as thermal runaway propagation.

Keywords: battery reliability, lithium-ion batteries, thermal runaway characterisation, tomography

Procedia PDF Downloads 102