Search results for: hybrid lattice Boltzmann method

Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

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Authors: Rajasekar Elangopandian, Anand Shanmugam

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In order to reduce the cost of launching satellite and payloads to the orbit this project envisages some immense combined technology. This new technology in space odyssey contains literally four concepts. The first mode in this innovation is flight mission characteristics which, says how the mission will induct. The conventional technique of magnetic levitation will help us to produce the initial thrust. The name states reusable launch vehicle shows its viability of reuseness. The flight consists miniature rocket which produces the required thrust and the two JATO (jet assisted takeoff) boosters which gives the initial boost for the vehicle. The vehicle ostensibly looks like an airplane design and will be located on the super conducting rail track. When the high power electric current given to the rail track, the vehicle starts floating as per the principle of magnetic levitation. If the flight reaches the particular takeoff distance the two boosters gets starts and will give the 48KN thrust each. Obviously it`ll follow the vertical path up to the atmosphere end/start to space. As soon as it gets its speed the two boosters will cutoff. Once it reaches the space the inbuilt spacecraft keep the satellite in the desired orbit. When the work finishes, the apogee motors gives the initial kick to the vehicle to come in to the earth’s atmosphere with 22N thrust and automatically comes to the ground by following the free fall, the help of gravitational force. After the flying region it makes the spiral flight mode then gets landing where the super conducting levitated rail track located. It will catch up the vehicle and keep it by changing the poles of magnets and varying the current. Initial cost for making this vehicle might be high but for the frequent usage this will reduce the launch cost exactly half than the now-a-days technology. The incorporation of such a mechanism gives `hybrid` and the reusability gives `reusable launch vehicle` and ultimately Hybrid reusable launch vehicle.

Keywords: the two JATO (jet assisted takeoff) boosters, magnetic levitation, 48KN thrust each, 22N thrust and automatically comes to the ground

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Authors: Mohamed Roudane

Abstract:

The objective of this study is to know the dynamic behavior of a multi swirling jet used for air conditioning inside a room. To conduct this study, we designed a facility to ensure proper conditions of confinement in which we placed five air blowing devices with adjustable vanes, providing multiple swirling turbulent jets. The jets were issued in the same direction and the same spacing defined between them. This study concerned the numerical simulation of the dynamic mixing of confined swirling multi-jets, and examined the influence of important parameters of a swirl diffuser system on the dynamic performance characteristics. The CFD investigations are carried out by a hybrid mesh to discretize the computational domain. In this work, the simulations have been performed using the finite volume method and FLUENT solver, in which the standard k-ε RNG turbulence model was used for turbulence computations.

Keywords: simulation, dynamic behavior, swirl, turbulent jet

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Authors: Seyedmajid Mehrnia, Maximilan Kuhr, Peter F. Pelz

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Molecular Dynamics (MD) simulation is a proven method to inspect behaviours of lubricant oils in nano-scale gaps. However, most MD simulations on tribology have been performed with atomically smooth walls to determine wall slip and friction properties. This study will investigate the effect of porosity, specifically nano-porous walls, on wall slip properties of hydrocarbon oils confined between two walls in a Couette flow. Different pore geometries will be modelled to investigate the effect on wall slip and bulk shear. In this paper, the Polyalphaolefin (PAO) molecules are confined to a stationary and a moving wall. A hybrid force field consisting of different potential energy functions was employed in this MD simulation. Newton’s law defines how those forces will influence the atoms' movements. The interactions among surface atoms were simulated with an Embedded Atom Method (EAM) potential function which can represent the characteristics of metallic arrangements very strongly. We implemented NERD forcefield for intramolecular potential energy function. Also, Lennard-Jones potential was employed for nonbonded intermolecular interaction.

Keywords: slip length, molecular dynamics, critical shear rate, Couette flow

Procedia PDF Downloads 132

Authors: Elvis Adam Alhassan, Kaiyu Tian, Akos Konadu, Ernest Zamanah, Michael Jackson Adjabui, Ibrahim Justice Musah, Esther Agyeiwaa Owusu, Emmanuel K. A. Agyeman

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In this paper, how to solve simultaneous equations using the Elvis improved method is shown. The Elvis improved method says; to make one variable in the first equation the subject; make the same variable in the second equation the subject; equate the results and simplify to obtain the value of the unknown variable; put the value of the variable found into one equation from the first or second steps and simplify for the remaining unknown variable. The difference between our Elvis improved method and the substitution method is that: with Elvis improved method, the same variable is made the subject in both equations, and the two resulting equations equated, unlike the substitution method where one variable is made the subject of only one equation and substituted into the other equation. After describing the Elvis improved method, findings from 100 secondary students and the views of 5 secondary tutors to demonstrate the effectiveness of the method are presented. The study's purpose is proved by hypothetical examples.

Keywords: simultaneous equations, substitution method, elimination method, graphical method, Elvis improved method

Procedia PDF Downloads 141

Authors: H. C. Woo, F. Bouanis, C. S. Cojocaur

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Graphene, which consists of a single layer of carbon atoms in a honeycomb lattice, is an interesting potential optoelectronic material because of graphene’s high carrier mobility, zero bandgap, and electron–hole symmetry. Graphene can absorb light and convert it into a photocurrent over a wide range of the electromagnetic spectrum, from the ultraviolet to visible and infrared regimes. Over the last several years, a variety of graphene-based photodetectors have been reported, such as graphene transistors, graphene-semiconductor heterojunction photodetectors, graphene based bolometers. It is also reported that there are several physical mechanisms enabling photodetection: photovoltaic effect, photo-thermoelectric effect, bolometric effect, photogating effect, and so on. In this work, we report a simple approach for the realization of graphene based resistive photo-detection devices and the measurements of their photoelectrical response. The graphene were synthesized directly on the glass substrate by novel growth method patented in our lab. Then, the metal electrodes were deposited by thermal evaporation on it, with an electrode length and width of 1.5 mm and 300 μm respectively, using Co to fabricate simple graphene based resistive photosensor. The measurements show that the graphene resistive devices exhibit a photoresponse to the illumination of visible light. The observed re-sistance response was reproducible and similar after many cycles of on and off operations. This photoelectrical response may be attributed not only to the direct photocurrent process but also to the desorption of oxygen. Our work shows that the simple graphene resistive devices have potential in photodetection applications.

Keywords: graphene, resistive sensor, optoelectronics, photoresponse

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Authors: Juan Manuel Real-Espinosa

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This paper addresses the first step to evaluate language learning apps: what theoretical framework to adopt when designing the app evaluation framework. The answer is not just one since there are several options that could be proposed. However, the question to be clarified is to what extent the learning design of apps is based on a specific learning approach, or on the contrary, on a fusion of elements from several theoretical proposals and paradigms, such as m-learning, mobile assisted language learning, and a number of theories about language acquisition. The present study suggests that the reality is closer to the second assumption. This implies that the theoretical framework against which the learning design of the apps should be evaluated must also be a hybrid theoretical framework, which integrates evaluation criteria from the different theories involved in language learning through mobile applications.

Keywords: mobile-assisted language learning, action-oriented approach, apps evaluation, post-method pedagogy, second language acquisition

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Authors: T. Häfele, J. Kaspar, M. Vielhaber, W. Calles, J. Griebsch

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The demand for an increasing diversification of the product spectrum associated with the current huge customization desire and subsequently the decreasing unit quantities of each production lot is gaining more and more importance within a great variety of industrial branches, e.g. automotive industry. Nevertheless, traditional product development and production processes (molding, extrusion) are already reaching their limits or fail to address these trends of a flexible and digitized production in view of a product variability up to lot size one. Thus, upcoming innovative production concepts like the additive manufacturing technology basically create new opportunities with regard to extensive potentials in product development (constructive optimization) and manufacturing (economic individualization), but mostly suffer from insufficient strength regarding structural components. Therefore, this contribution presents an innovative technological and procedural conception of a hybrid additive manufacturing process (fiber-reinforced sandwich structures based on selective laser sintering technology) to overcome these current structural weaknesses, and consequently support the design of complex lightweight components.

Keywords: additive manufacturing, fiber-reinforced plastics (FRP), hybrid design, lightweight design

Procedia PDF Downloads 297

Authors: Bharath Kenchappa, Kunigal Shivakumar

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Lightweight, low thermal conductivity and high temperature resistant materials or the system with moderate mechanical properties and capable of taking high heating rates are needed in both commercial and military applications. A single material with these attributes is very difficult to find and one needs to come with innovative ideas to make such material system using what is available. To bring down the cost of the system, one has to be conscious about the cost of basic materials. Such a material system can be called as the thermal barrier system. This paper focuses on developing, testing and characterization of material system for thermal barrier applications. The material developed is porous, low density, low thermal conductivity of 0.1062 W/m C and glass transition temperature about 310 C. Also, the thermal properties of the developed material was measured in both longitudinal and thickness direction to highlight the fact that the material shows isotropic behavior. The material is called modified Eco-Core which uses only less than 9% weight of high-char resin in the composite. The filler (reinforcing material) is a component of fly ash called Cenosphere, they are hollow micro-bubbles made of ceramic materials. Special mixing-technique is used to surface coat the fillers with a thin layer of resin to develop a point-to-point contact of particles. One could use commercial ceramic micro-bubbles instead of Cenospheres, but it is expensive. The bulk density of Cenospheres is about 0.35 g/cc and we could accomplish the composite density of about 0.4 g/cc. One percent filler weight of 3mm length standard drywall grade fibers was used to bring the added toughness. Both thermal and mechanical characterization was performed and properties are documented. For higher temperature applications (up to 1,000 C), a hybrid system was developed using an aerogel mat. Properties of combined material was characterized and documented. Thermal tests were conducted on both the bare modified Eco-Core and hybrid materials to assess the suitability of the material to a thermal barrier application. The hybrid material system was found to meet the requirement of the application.

Keywords: aerogel, fly ash, porous material, thermal barrier

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Seyed Javad Vaziri Kang Olyaei, Asma Sadat Dabiri, Hassan Fazaeli, Amir Ali Amini

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Cracks in concrete pavements are places for the entrance of water and corrosive substances to the pavement, which can reduce the durability of concrete in the long term as well as the serviceability of road. The use of fibers in concrete pavement is one of the effective methods to control and mitigate cracking. This study investigates the effect of the addition of micro and macro polypropylene fibers in different types and volumes and also in combination with the mechanical properties of concrete used in concrete pavements, including compressive strength, splitting tensile strength, modulus of rupture, and average residual strength. The fibers included micro-polypropylene, macro-polypropylene, and hybrid micro and micro polypropylene in different percentages. The results showed that macro polypropylene has the most significant effect on improving the mechanical properties of concrete. Also, the hybrid micro and macro polypropylene fibers increase the mechanical properties of concrete more. It was observed that according to the results of the average residual strength, macro polypropylene fibers alone and together with micro polypropylene fibers could have excellent performance in controlling the sudden formation of cracks and their growth after the formation of cracking which is an essential property in concrete pavements.

Keywords: concrete pavement, mechanical properties, macro polypropylene fibers, micro polypropylene fibers

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Selcen Nur Eri̇kci̇ Çeli̇k, Burcu İbaş Parlakyildiz, Gülay Zorer Gedi̇k

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Reducing the use of mechanical heating and cooling systems in buildings, which accounts for approximately 30-40% of total energy consumption in the world has a major impact in terms of energy conservation. Formations of buildings that have sustainable and low energy utilization, structural elements with mechanical systems should be evaluated with a holistic approach. In point of reduction of building energy consumption ratio, wall elements that are vertical building elements and have an area broadly (m2) have proposed as a regulation with a different system. In the study, designing surface heating and cooling energy with a hybrid type of modular wall system and the integration of building elements will be evaluated. The design of wall element; - Identification of certain standards in terms of architectural design and size, -Elaboration according to the area where the wall elements (interior walls, exterior walls) -Solution of the joints, -Obtaining the surface in terms of building compatible with both conceptual structural put emphasis on upper stages, these elements will be formed. The durability of the product to the various forces, stability and resistance are so much substantial that are used the establishment of ready-wall element section and the planning of structural design. All created ready-wall alternatives will be paid attention at some parameters; such as adapting to performance-cost by optimum level and size that can be easily processed and reached. The restrictions such as the size of the zoning regulations, building function, structural system, wheelbase that are imposed by building laws, should be evaluated. The building aims to intend to function according to a certain standardization system and construction of wall elements will be used. The scope of performance criteria determined on the wall elements, utilization (operation, maintenance) and renovation phase, alternative material options will be evaluated with interim materials located in the contents. Design, implementation and technical combination of modular wall elements in the use phase and installation details together with the integration of energy saving, heat-saving and useful effects on the environmental aspects will be discussed in detail. As a result, the ready-wall product with surface heating and cooling modules will be created and defined as hybrid wall and will be compared with the conventional system in terms of thermal comfort. After preliminary architectural evaluations, certain decisions for all architectural design processes (pre and post design) such as the implementation and performance in use, maintenance, renewal will be evaluated in the results.

Keywords: modular ready-wall element, hybrid, architectural design, thermal comfort, energy saving

Procedia PDF Downloads 255

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 76

Authors: Arezoo Hakimi, Afshin Farahbakhsh

Abstract:

Herein, we comparison synthesized Fe3O4 using, hydrothermal method, Mechanochemical processes and solvent thermal method. The Hydrothermal Technique has been the most popular one, gathering interest from scientists and technologists of different disciplines, particularly in the last fifteen years. In the hydrothermal method Fe3O4 microspheres, in which many nearly monodisperse spherical particles with diameters of about 400nm, in the mechanochemical method regular morphology indicates that the particles are well crystallized and in the solvent thermal method Fe3O4 nanoparticles have good properties of uniform size and good dispersion.

Keywords: Fe3O4 nanoparticles, hydrothermal method, mechanochemical processes, solvent thermal method

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

Procedia PDF Downloads 119

Authors: Autcha Araveeporn

Abstract:

This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

Procedia PDF Downloads 440

Authors: Mohammed Habchi, Sidi Mohammed Mesli, Rafik Benallal, Mohammed Kotbi

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On the basis of four partial correlation functions and some geometric constraints obtained from neutron scattering experiments, a Reverse Monte Carlo (RMC) simulation has been performed in the study of the aqueous electrolyte LiCl6H2O at the glassy state. The obtained 3-dimensional model allows computing pair radial and orientational distribution functions in order to explore the structural features of the system. Unrealistic features appeared in some coordination peaks. To remedy to this, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an additional energy constraint in addition to the usual constraints derived from experiments. The energy of the system is calculated using an Environment Dependence Interaction Potential (EDIP). Ions effects is studied by comparing correlations between water molecules in the solution and in pure water at room temperature Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in orientational distribution curves.

Keywords: LiCl6H2O, glassy state, RMC, HRMC

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Authors: Anna Crivellari, Valerio Cozzani

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Even though most of the electricity produced in the entire world still comes from fossil fuels, new policies are being implemented in order to promote a more sustainable use of energy sources. Offshore renewable resources have become increasingly attractive thanks to the huge entity of power potentially obtained. However, the intermittent nature of renewables often limits the capacity of the systems and creates mismatches between supply and demand. Hydrogen is foreseen to be a promising vector to store and transport large amounts of excess renewable power by using existing oil and gas infrastructure. In this work, an offshore hybrid energy system integrating wind energy conversion with hydrogen production was conceptually defined and applied to offshore gas platforms. A techno-economic analysis was performed by considering two different locations for the installation of the innovative power system, i.e., the North Sea and the Adriatic Sea. The water depth, the distance of the platform from the onshore gas grid, the hydrogen selling price and the green financial incentive were some of the main factors taken into account in the comparison. The results indicated that the use of well-defined indicators allows to capture specifically different cost and revenue features of the analyzed systems, as well as to evaluate their competitiveness in the actual and future energy market.

Keywords: cost analysis, energy efficiency assessment, hydrogen production, offshore wind energy

Procedia PDF Downloads 126

Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Bahare Askarian, Suchithra Rajendran

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Maintaining the freshness and quality of perishable goods during distribution is a critical challenge for logistics companies. This study presents a comprehensive framework aimed at optimizing the distribution of perishable goods through a mathematical model of the Transportation Inventory Location Routing Problem (TILRP). The model incorporates the impact of product age on customer demand, addressing the complexities associated with inventory management and routing. To tackle this problem, we develop both simple and hybrid metaheuristic algorithms designed for small- and medium-scale scenarios. The hybrid algorithm combines Biogeographical Based Optimization (BBO) algorithms with local search techniques to enhance performance in small- and medium-scale scenarios, extending our approach to larger-scale challenges. Through extensive numerical simulations and sensitivity analyses across various scenarios, the performance of the proposed algorithms is evaluated, assessing their effectiveness in achieving optimal solutions. The results demonstrate that our algorithms significantly enhance distribution efficiency, offering valuable insights for logistics companies striving to improve their perishable goods supply chains.

Keywords: perishable goods, meta-heuristic algorithm, vehicle problem, inventory models

Procedia PDF Downloads 23

Authors: F. A. M. Safwan, H. N. N. Dilrukshi, P. U. S. Peiris

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Less availability of high quality green forages leads to low productivity of national dairy herd of Sri Lanka. Growing grass and fodder to suit the production system is an efficient and economical solution for this problem. CO-3 is placed in a higher category, especially on tillering capacity, green forage yield, regeneration capacity, leaf to stem ratio, high crude protein content, resistance to pests and diseases and free from adverse factors along with other fodder varieties grown within the country. An experiment was designed to determine the effect of organic sheep manure, inorganic fertilizers and liquid sheep manure on growth, yield and nutritive value of CO-3. The study was consisted with three treatments; sheep manure (T1), recommended inorganic fertilizers (T2) and liquid sheep manure (T3) which was prepared using bucket fermentation method and each treatment was consisted with three replicates and those were assigned randomly. First harvest was obtained after 40 days of plant establishment and number of leaves (NL), leaf area (LA), tillering capacity (TC), fresh weight (FW) and dry weight (DW) were recorded and second harvest was obtained after 30 days of first harvest and same set of data were recorded. SPSS 16 software was used for data analysis. For proximate analysis AOAC, 2000 standard methods were used. Results revealed that the plants treated with T1 recorded highest NL, LA, TC, FW and DW and were statistically significant at first and second harvest of CO-3 (p˂ 0.05) and it was found that T1 was statistically significant from T2 and T3. Although T3 was recorded higher than the T2 in almost all growth parameters; it was not statistically significant (p ˃0.05). In addition, the crude protein content was recorded highest in T1 with the value of 18.33±1.61 and was lowest in T2 with the value of 10.82±1.14 and was statistically significant (p˂ 0.05). Apart from this, other proximate composition crude fiber, crude fat, ash, moisture content and dry matter were not statistically significant between treatments (p ˃0.05). In accordance with the results, it was found that the organic fertilizer is the best fertilizer for CO-3 in terms of growth parameters and crude protein content.

Keywords: fertilizer, growth parameters, Hybrid Napier CO-3, proximate composition

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Authors: Karthika Chandran, Pulkit Prakash, Amitabh Das, Santhosh P. N.

Abstract:

Rare earth orthoferrites (RFeO₃) exhibit interesting and useful magnetic properties like multiferroicity, magnetodielectric coupling, spin reorientation (SR) and exchange bias. B site doped RFeO₃ are attracting attention due to the complex and tuneable magnetic transitions. In this work, 45% Mn-doped HoFeO₃ polycrystalline sample (HoFe₀.₅₅Mn₀.₄₅O₃) was synthesized by a solid-state reaction method. The magnetic structure and transitions were studied by magnetization measurements and neutron powder diffraction methods. The neutron diffraction patterns were taken at 13 different temperatures from 7°K to 300°K (7°K and 25°K to 300°K in 25°K intervals). The Rietveld refinement was carried out by using a FULLPROF suite. The magnetic space groups and the irreducible representations were obtained by SARAh module. The room temperature neutron diffraction refinement results indicate that the sample crystallizes in an orthorhombic perovskite structure with Pnma space group with lattice parameters a = 5.6626(3) Ǻ, b = 7.5241(3) Ǻ and c = 5.2704(2) Ǻ. The temperature dependent magnetization (M-T) studies indicate the presence of two magnetic transitions in the system ( TN Fe/Mn~330°K and TSR Fe/Mn ~290°K). The inverse susceptibility vs. temperature curve shows a linear behavior above 330°K. The Curie-Weiss fit in this region gives negative Curie constant (-34.9°K) indicating the antiferromagnetic nature of the transition. The neutron diffraction refinement results indicate the presence of mixed magnetic phases Γ₄(AₓFᵧG

Keywords: neutron powder diffraction, rare earth orthoferrites, Rietveld analysis, spin reorientation

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Authors: S. Oladoyinbo, A. A. Tijani

Abstract:

Multilevel inverters (MLI) are used at high power application based on their operation. There are 3 main types of multilevel inverters (MLI); diode clamped, flying capacitor and cascaded MLI. A cascaded MLI requires the least number of components to achieve same number of voltage levels when compared to other types of MLI while the flying capacitor has the minimum harmonic distortion. However, maximizing the advantage of cascaded H-bridge MLI and flying capacitor MLI, an improved MLI can be achieved with fewer components and better performance. In this paper an improved MLI is presented by asymmetrically integrating a flying capacitor to a cascaded H-bridge MLI also integrating an auxiliary transformer to the main transformer to decrease the total harmonics distortion (THD) with increased number of output voltage levels. Furthermore, the system is incorporated with a hybrid time and climate based solar panel cleaner and power selector which intelligently manage the input of the MLI and clean the solar panel weekly ensuring the environmental factor effect on the panel is reduced to minimum.

Keywords: multilevel inverter, total harmonics distortion, cascaded h-bridge inverter, flying capacitor

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Authors: Ugwu Elias Ikechukwu

Abstract:

Discussions on bilingualism have always dwelt on how the mother tongue interferes with the target language. This interference is considered a serious problem in second language learning. Usually, the interference has been phonological. But the objective of this research is to explore how the target language interferes with the mother tongue. In the case of the Igbo language, it interferes with English mostly at the phonological level while English interferes with Igbo at the realm of vocabulary. The result is a new language \"Engligbo\" which is a hybrid of English and Igbo. The Igbo language spoken by about 25 million people is one of the three most prominent languages in Nigeria. This paper discusses the phenomenal Engligbo, and other implications for Igbo learners of English. The method of analysis is descriptive. A number of recommendations were made that would help teachers handle problems arising from such mutual interferences.

Keywords: reciprocal interferences, bilingualism, implications, language pedagogy

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Authors: A. Derrouazin, N. Mekkakia-M, R. Taleb, M. Helaimi, A. Benbouali

Abstract:

Nowadays the use of different sources of renewable energy for the production of electricity is the concern of everyone, as, even impersonal domestic use of the electricity in isolated sites or in town. As the conventional sources of energy are shrinking, a need has arisen to look for alternative sources of energy with more emphasis on its optimal use. This paper presents design of a sustainable Hybrid Power System (PV-Wind-Storage) assisted by grid as supplementary sources applied to case study residential house, to meet its entire energy demand. A Fuzzy control system model has been developed to optimize and control flow of power from these sources. This energy requirement is mainly fulfilled from PV and Wind energy stored in batteries module for critical load of a residential house and supplemented by grid for base and peak load. The system has been developed for maximum daily households load energy of 3kWh and can be scaled to any higher value as per requirement of individual /community house ranging from 3kWh/day to 10kWh/day, as per the requirement. The simulation work, using intelligent energy management, has resulted in an optimal yield leading to average reduction in cost of electricity by 50% per day.

Keywords: photovoltaic (PV), wind turbine, battery, microcontroller, fuzzy control (FC), Matlab

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Authors: Abderrahmane Hamdi, Julie Chalon, Benoit Dodin, Philippe Champagne

Abstract:

In this report, we present a simple route to realize robust, hydrophobic, and highly transparent coatings using organic polysilazane (durazane) and zinc oxide nanoparticles (ZnO). These coatings were deposited by spraying the mixture solution on glass slides. Thus, the properties of the films were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), UV–vis-NIR spectrophotometer, and water contact angle method. This sprayable polymer mixed with ZnO nanoparticles shows high transparency for visible light > 90%, a hydrophobic character (CA > 90°), and good mechanical and chemical stability. The coating also demonstrates excellent self-cleaning properties, which makes it a promising candidate for commercial use.

Keywords: coatings, durability, hydrophobicity, organic polysilazane, self-cleaning, transparence, zinc oxide nanoparticles

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Authors: Delara Soltani, Sajad Alimohammadi, Tim Persoons

Abstract:

Microfluidic technology reveals a new area of research in drug delivery, biomedical diagnostics, and the food and chemical industries. Mixing is an essential part of microfluidic devices. There is a need for fast and homogeneous mixing in microfluidic devices. On the other hand, mixing is difficult to achieve in microfluidic devices because of the size and laminar flow in these devices. In this study, a hybrid passive micromixer of a curved channel with obstacles inside the channel is designed. The computational fluid dynamic method is employed to solve governing equations. The results show that using obstacles can improve mixing efficiency in spiral micromixers. the effects of Reynolds number, number, and position of baffles are investigated. In addition, the effect of baffles on pressure drop is presented. this novel micromixer has the potential to utilize in microfluidic devices.

Keywords: CFD, micromixer, microfluidics, spiral, reynolds number

Procedia PDF Downloads 91