Search results for: multi phase failure

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

Procedia PDF Downloads 223

Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj K. Biswas, Frank Ferrese

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This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

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Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

Procedia PDF Downloads 445

Authors: Jonggeon Lee, Sungho Tae, Sungjoon Suk, Keunhyeok Yang, George Ford, Michael E. Smith, Omidreza Shoghli

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In recent years, research to reduce carbon emissions through quantitative assessment of building life cycle carbon emissions has been performed as it relates to the construction industry. However, most research efforts related to building carbon emissions assessment have been focused on evaluation during the operational phase of a building’s life span. Few comprehensive studies of the carbon emissions during a building’s construction phase have been performed. The purpose of this study is to propose an assessment method that quantitatively evaluates the carbon emissions of buildings during the construction phase. The study analysed the amount of carbon emissions produced by 17 construction trades, and selected four construction trades that result in high levels of carbon emissions: reinforced concrete work; sheathing work; foundation work; and form work. Building materials, and construction and transport equipment used for the selected construction trades were identified, and carbon emissions produced by the identified materials and equipment were calculated for these four construction trades. The energy consumption of construction and transport equipment was calculated by analysing fuel efficiency and equipment productivity rates. The combination of the expected levels of carbon emissions associated with the utilization of building materials and construction equipment provides means for estimating the quantity of carbon emissions related to the construction phase of a building’s life cycle. The proposed carbon emissions assessment method was validated by case studies.

Keywords: building construction phase, carbon emissions assessment, building life cycle

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Authors: Habtamu Tkubet Ebuy

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Purpose Conventional dynamic energy simulation tools go beyond the static dimension of simplified methods by providing better and more accurate prediction of building performance. However, their ability to forecast actual performance is undermined by a low representation of human interactions. The purpose of this study is to examine the potential benefits of incorporating information on occupant diversity into occupant behavior models used to simulate building performance. The co-simulation of the stochastic behavior of the occupants substantially increases the accuracy of the simulation. Design/methodology/approach In this article, probabilistic models of the "opening and closing" behavior of the window of inhabitants have been developed in a separate multi-agent platform, SimOcc, and implemented in the building simulation, TRNSYS, in such a way that the behavior of the window with the interconnectivity can be reflected in the simulation analysis of the building. Findings The results of the study prove that the application of complex behaviors is important to research in predicting actual building performance. The results aid in the identification of the gap between reality and existing simulation methods. We hope this study and its results will serve as a guide for researchers interested in investigating occupant behavior in the future. Research limitations/implications Further case studies involving multi-user behavior for complex commercial buildings need to more understand the impact of the occupant behavior on building performance. Originality/value This study is considered as a good opportunity to achieve the national strategy by showing a suitable tool to help stakeholders in the design phase of new or retrofitted buildings to improve the performance of office buildings.

Keywords: occupant behavior, co-simulation, energy consumption, thermal comfort

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Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

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In this paper, a new neural network based variable neighborhood search is proposed for the multi-objective dynamic, flexible job shop scheduling problems. The neural network controls the problems' constraints to prevent infeasible solutions, while the Variable Neighborhood Search (VNS) applies moves, based on the critical block concept to improve the solutions. Two approaches are used for managing the constraints, in the first approach, infeasible solutions are modified according to the constraints, after the moves application, while in the second one, infeasible moves are prevented. Several neighborhood structures from the literature with some modifications, also new structures are used in the VNS. The suggested neighborhoods are more systematically defined and easy to implement. Comparison is done based on a multi-objective flexible job shop scheduling problem that is dynamic because of the jobs different release time and machines breakdowns. The results show that the presented method has better performance than the compared VNSs selected from the literature.

Keywords: constrained optimization, neural network, variable neighborhood search, flexible job shop scheduling, dynamic multi-objective optimization

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Authors: Erhan Ayas, Buse Katipoğlu, Eda Metin, Rifat Yılmaz

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The search for new materials has begun to be used even higher than the service temperature (~1150ᵒC) where nickel-based superalloys are currently used. This search should also meet the increasing demands for energy efficiency improvements. The materials studied for aerospace applications are expected to have good oxidation resistance. Mo-Si-B alloys, which have higher operating temperatures than nickel-based superalloys, are candidates for ultra-high temperature materials used in gas turbine and jet engines. Because the Moss and Mo₅SiB₂ (T2) phases exhibit high melting temperature, excellent high-temperature creep strength and oxidation resistance properties, however, low fracture toughness value at room temperature is a disadvantage for these materials, but this feature can be improved with optimum Moss phase and microstructure control. High-density value is also a problem for structural parts. For example, in turbine rotors, the higher the weight, the higher the centrifugal force, which reduces the creep life of the material. The density value of the nickel-based superalloys and the T2 phase, which is the Mo-Si-B alloy phase, is in the range of 8.6 - 9.2 g/cm³. But under these conditions, T2 phase Moss (density value 10.2 g/cm³), this value is above the density value of nickel-based superalloys. So, with some ceramic-based contributions, this value is enhanced by optimum values.

Keywords: molybdenum, composites, in-situ, mmc

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

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The design of Reverse logistics Network has attracted growing attention with the stringent pressures from both environmental awareness and business sustainability. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict, and decision making is one of the challenges tasks. This complexity has amplified the need to develop an integrated architecture for product return as an enterprise system. The main purpose of this paper is to design Multi agent system (MAS) architecture using the Prometheus methodology to efficiently manage reverse logistics processes. The proposed MAS architecture includes five types of agents: Gate keeping Agent, Collection Agent, Sorting Agent, Processing Agent and Disposal Agent which act respectively during the five steps of reverse logistics Network.

Keywords: reverse logistics, multi agent system, prometheus methodology

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Authors: Karthick Prasad Gunasekaran, B. Chase Babrich, Saurabh Shirodkar, Hee Hwang

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Construction preparation is crucial for the success of a construction project. By involving project participants early in the construction phase, project managers can plan ahead and resolve issues early, resulting in project success and satisfaction. This study uses quantitative data from construction management projects to determine the relationship between the pre-construction phase, construction schedule, and customer satisfaction. This study examined a total of 65 construction projects and 93 clients per job to (a) identify the relationship between the pre-construction phase and program reduction and (b) the pre-construction phase and customer retention. Based on a quantitative analysis, this study found a negative correlation between pre-construction status and project schedule in 65 construction projects. This finding means that the more preparatory work done on a particular project, the shorter the total construction time. The Net Promoter Score of 93 clients from 65 projects was then used to determine the relationship between construction preparation and client satisfaction. The pre-construction status and the projects were further analyzed, and a positive correlation between them was found. This shows that customers are happier with projects with a higher ready-to-build ratio than projects with less ready-to-build.

Keywords: NLP, BERT, LLM, deep learning, classification

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Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

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The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

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Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: ChoLiang Chung, YuMin Chen

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C-doped TiO2 nanofibers were prepared by electrospinning successfully. Different amounts of carbon were added into the nanofibers by using chitosan, aiming to shift the wave length that is required to excite the photocatalyst from ultraviolet light to visible light. Different amounts of carbon and different atmosphere fibers were calcined at 500oC, and the optical characteristic of C-doped TiO2 nanofibers had been changed. characterizes of nanofibers were identified by X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FE-SEM), UV-vis, Atomic Force Microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). The XRD is used to identify the phase composition of nanofibers. The morphology of nanofibers were explored by FE-SEM and AFM. Optical characteristics of absorption were measured by UV-Vis. Three dimension surface images of C-doped TiO2 nanofibers revealed different effects of processing. The results of XRD showed that the phase of C-doped TiO2 nanofibers transformed to rutile phase and anatase phase successfully. The results of AFM showed that the surface morphology of nanofibers became smooth after high temperature treatment. Images from FE-SEM revealed the average size of nanofibers. UV-vis results showed that the band-gap of TiO2 were reduced. Finally, we found out C-doped TiO2 nanofibers can change countenance of nanofiber and make it smoother.

Keywords: carbon, TiO2, chitosan, electrospinning

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Authors: Dao Phuong Nam, Do Trong Tan, Pham Tam Thanh, Le Duy Tung, Tran Hoang Anh

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This paper considers the problem of cascade control system for unmanned aerial vehicles (UAVs). Due to the complicated modelling technique of UAV, it is necessary to separate them into two subsystems. The proposed cascade control structure is a hierarchical scheme including a robust control for inner subsystem based on H infinity theory and trajectory generator using genetic algorithm (GA), outer loop control law based on multi-parametric programming (MPP) technique to overcome the disadvantage of a big amount of calculations. Simulation results are presented to show that the equivalent path has been found and obtained by proposed cascade control scheme.

Keywords: genetic algorithm, GA, H infinity, multi-parametric programming, MPP, unmanned aerial vehicles, UAVs

Procedia PDF Downloads 201

Authors: Atabak Rashidian

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In duplex backhaul wireless communication systems, two separate transmit and receive high-gain antennas are required if an antenna switch is not implemented. Although the switch loss, which is considerable and in the order of 1.5 dB at 60 GHz, is avoided, the large separate antenna systems make the design bulky and not cost-effective. To avoid two large reflectors for such a system, transmit and receive antenna feeds with a common phase center are required. The phase center should coincide with the focal point of the reflector to maximize the efficiency and gain. In this work, we present an ultra-compact design in which stacked patch antennas are used as the feeds for a 12-inch reflector. The transmit antenna is a 1 × 2 array and the receive antenna is a single element located in the middle of the transmit antenna elements. Antenna elements are designed as stacked patches to provide the required impedance bandwidth for four standard channels of WiGigTM applications. The design includes three metallic layers and three dielectric layers, in which the top dielectric layer is a 100 µm-thick protective layer. The top two metallic layers are specified to the main and parasitic patches. The bottom layer is basically ground plane with two circular openings (0.7 mm in diameter) having a center through via which connects the antennas to a single input/output Si-Ge Bi-CMOS transceiver chip. The reflection coefficient of the stacked patch antenna is fully investigated. The -10 dB impedance bandwidth is about 11%. Although the gap between transmit and receive antenna is very small (g = 0.525 mm), the mutual coupling is less than -12 dB over the desired frequency band. The three dimensional radiation patterns of the transmit and receive reflector antennas at 60 GHz is investigated over the impedance bandwidth. About 39 dBi realized gain is achieved. Considering over 15 dBm of output power of the silicon chip in the transmit side, the EIRP should be over 54 dBm, which is good enough for over one kilometer multi Gbps data communications. The performance of the reflector antenna over the bandwidth shows the peak gain is 39 dBi and 40 dBi for the reflector antenna with 2-element and single element feed, respectively. This type of the system design is cost-effective and efficient.

Keywords: Antenna, integrated circuit, millimeter-wave, phase center

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Authors: Fatema-Tuz-Zahura, Raquib Ahsan

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Punching shear failure is usually the governing failure mode of flat plate structures. Punching failure is brittle in nature which induces more vulnerability to this type of structure. In the present study, a 3D finite element model of a flat plate with low reinforcement ratio and without any transverse reinforcement has been developed. Punching shear stress and the deflection data were obtained on the surface of the flat plate as well as through the thickness of the model from numerical simulations. The obtained data were compared with the experimental results. Variation of punching stress with respect to deflection as obtained from numerical results is found to be in good agreement with the experimental results; the range of variation of punching stress is within 5%. The numerical simulation shows an early and gradual onset of nonlinearity, whereas the same is late and abrupt as observed in the experimental results. The range of variation of punching stress for different slab thicknesses between experimental and numerical results is less than 15%. The developed numerical model is useful to complement available punching test series performed in the past. The results obtained from the numerical model will be helpful for designing retrofitting schemes of flat plates.

Keywords: flat plate, finite element model, punching shear, reinforcement ratio

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Authors: Wael M. El-Deeb

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The aim of this study was to assess the pathophysiological importance of lipid profile, acute phase proteins, proinflammatory cytokines and oxidative stress markers in sheep with pneumonic pasteurellosis. Blood samples were collected from 36 Pasteurellamultocida-infected sheep, together with 20 healthy controls. Samples for bacteriological examination (nasal swabs, bronchoalveolar lavage) were collected from all animals and subjected to bacteriological examinations. Moreover, heart blood and lung samples were collected from the dead pneumonic sheep and subjected also to bacteriological examinations. A lipid profile was determined, along with a blood picture and other biochemical parameters. The acute phase proteins (fibrinogen, haptoglobin, serum amyloid A), the proinflammatory cytokine tumour necrosis factor-alpha, interleukins (IL-1α, IL-1β, IL-6), interferon-gamma and the oxidative stress markers malondialdehyde, super oxide dismutase, glutathione and catalase were also measured. The examined biochemical parameters were increased in the pneumonic sheep, except for cholesterol and high-density lipoprotein cholesterol (HDL-c), which were significantly lower than control group. Acute phase proteins and cytokines were significantly higher in the pneumonic sheep when compared to the healthy sheep. There was a significant increase in the levels of malondialdehyde; however, a significant decrease in the levels of super oxide dismutase, glutathione and catalase was observed. The present study shed the light on the possible pathphysiological role of lipid profile, acute phase proteins (APPs), proinflammatory cytokines and oxidative stress markers in pneumonic pasteurelosis in sheep.

Keywords: acute phase proteins, sheep, pasteurella, interleukins, stress

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Authors: Ilze Dimanta, Zane Rutkovska, Vizma Nikolajeva, Janis Kleperis, Indrikis Muiznieks

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Majority of word’s steadily increasing energy consumption is provided by non-renewable fossil resources. Need to find an alternative energy resource is essential for further socio-economic development. Hydrogen is renewable, clean energy carrier with high energy density (142 MJ/kg, accordingly – oil has 42 MJ/kg). Biological hydrogen production is an alternative way to produce hydrogen from renewable resources, e.g. using organic waste material resource fermentation that facilitate recycling of sewage and are environmentally benign. Hydrogen gas is produced during the fermentation process of bacteria in anaerobic conditions. Bacteria are producing hydrogen in the liquid phase and when thermodynamic equilibrium is reached, hydrogen is diffusing from liquid to gaseous phase. Because of large quantities of available crude glycerol and the highly reduced nature of carbon in glycerol per se, microbial conversion of it seems to be economically and environmentally viable possibility. Such industrial organic waste product as crude glycerol is perspective for usage in feedstock for hydrogen producing bacteria. The process of biodiesel production results in 41% (w/w) of crude glycerol. The developed lab-scale test system (experimental bioreactor) with hydrogen micro-electrode (Unisense, Denmark) was used to determine hydrogen production yield and rate in the liquid phase. For hydrogen analysis in the gas phase the RGAPro-100 mass-spectrometer connected to the experimental test-system was used. Fermentative bacteria strains were tested for hydrogen gas production rates. The presence of hydrogen in gaseous phase was measured using mass spectrometer but registered concentrations were comparatively small. To decrease the hydrogen partial pressure in liquid phase reactor with a system for continuous bubbling with inert gas was developed. H2 production rate for the best producer in liquid phase reached 0,40 mmol H2/l, in gaseous phase - 1,32 mmol H2/l. Hydrogen production rate is time dependent – higher rate of hydrogen production is at the fermentation process beginning when concentration increases, but after three hours of fermentation, it decreases.

Keywords: bio-hydrogen, fermentation, experimental bioreactor, crude glycerol

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Authors: Subodh N. Patel, Abhijit Pusty, Manashi Adhikary, Sandip Bhattacharyya

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The steam superheater (SH) is a coil type heat exchanger which is used to produce superheated steam or to convert the wet steam to dry steam (69.6 kg/cm² and 495°C), generated by a boiler. There were two superheaters in the system, SH I and SH II. SH II is a set of tubes that faces the initial interaction with flue gas at high temperature followed by SH I tubes. After a service life of 2100 hours, a tube in the SH II found to be punctured. Dye penetrant test revealed that out of 50 such tubes, 14 more tubes had severe cracks at a similar location. The failure was investigated in detail. The materials and scale were characterized by optical microscope and advance characterization technique. Scale, observed on fracture surface, was characterized under scanning electron microscope and Raman spectroscopy. Stresses acting on the tubes in working condition were analyzed by finite element method software, ANSYS. Cyclic stresses were observed in the simulation at the same prone location due to restriction in expansion of tubes. Based on scale characterization and stress analysis, it was concluded that the tube failed in thermo-mechanical fatigue. Finally, prevention and control measures were taken to avoid such failure in the future.

Keywords: finite element analysis, oxide scale, superheater tube, thermomechanical fatigue

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Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

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Authors: Julio C. Ferreira, Maria T. A. Steiner

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The aim of this work is to present a solution procedure referred to here as the Multi-objective Optimization for Green Vehicle Routing Problem (MOOGVRP) to provide solutions for a case study. The proposed methodology consists of three stages to resolve Scenario A. Stage 1 consists of the “treatment” of data; Stage 2 consists of applying mathematical models of the p-Median Capacitated Problem (with the objectives of minimization of distances and homogenization of demands between groups) and the Asymmetric Traveling Salesman Problem (with the objectives of minimizing distances and minimizing time). The weighted method was used as the multi-objective procedure. In Stage 3, an analysis of the results is conducted, taking into consideration the environmental aspects related to the case study, more specifically with regard to fuel consumption and air pollutant emission. This methodology was applied to a (partial) database that addresses newspaper distribution in the municipality of Curitiba, Paraná State, Brazil. The preliminary findings for Scenario A showed that it was possible to improve the distribution of the load, reduce the mileage and the greenhouse gas by 17.32% and the journey time by 22.58% in comparison with the current scenario. The intention for future works is to use other multi-objective techniques and an expanded version of the database and explore the triple bottom line of sustainability.

Keywords: Asymmetric Traveling Salesman Problem, Green Vehicle Routing Problem, Multi-objective Optimization, p-Median Capacitated Problem

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Authors: Serhat Tüzün, Tufan Demirel

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The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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Authors: N. Li, Y. M. Cheng

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In this paper, the classical bearing capacity problem is re-considered from discrete element analysis. In the discrete element approach, the bearing capacity problem is considered from the elastic stage to plastic stage to rupture stage (large displacement). The bearing capacity failure mechanism of a strip footing on soil is investigated, and the influence of micro-parameters on the bearing capacity of soil is also observed. It is found that the distinct element method (DEM) gives very good visualized results, and basically coincides well with that derived by the classical methods.

Keywords: bearing capacity, distinct element method, failure mechanism, large displacement

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Authors: Andres Pinilla Palacios, Ricardo Tamayo

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Emotional contagion is characterized as an automatic tendency to synchronize behaviors that facilitate emotional convergence among humans. It might thus play a pivotal role to understand the dynamics of key social interactions. However, a few research has investigated its potential mechanisms. We suggest two complementary but independent processes that may underlie emotional contagion. The efficient contagion hypothesis, based on fast and implicit bottom-up processes, modulated by familiarity and spread of activation in the emotional associative networks of memory. Secondly, the emotional contrast hypothesis, based on slow and explicit top-down processes guided by deliberated appraisal and hypothesis-testing. In order to assess these two hypotheses, an experiment with 39 participants was conducted. In the first phase, participants were induced (between-groups) to an emotional state (positive, neutral or negative) using a standardized video taken from the FilmStim database. In the second phase, participants classified and rated (within-subject) the emotional state of 15 faces (5 for each emotional state) taken from the POFA database. In the third phase, all participants were returned to a baseline emotional state using the same neutral video used in the first phase. In a fourth phase, participants classified and rated a new set of 15 faces. The accuracy in the identification and rating of emotions was partially explained by the efficient contagion hypothesis, but the speed with which these judgments were made was partially explained by the emotional contrast hypothesis. However, results are ambiguous, so a follow-up experiment is proposed in which emotional expressions and activation of the sympathetic system will be measured using EMG and EDA respectively.

Keywords: electromyography, emotional contagion, emotional valence, identification of emotions, imitation

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Authors: Swati Sundararajan, , Asit B. Samui, Prashant S. Kulkarni

Abstract:

The global energy crisis has led to extensive research on alternative sources of energy. The gap between energy supply and demand can be met by thermal energy storage techniques, of which latent heat storage is most effective in the form of phase change materials (PCMs). Phase change materials utilize latent heat absorbed or released over a narrow temperature range of the material undergoing phase transformation, to store energy. The latent heat can be utilized for heating or cooling purposes. It can also be used for converting to electricity. All these actions amount to minimizing the load on electricity demand. These materials retain this property over repeated number of cycles. Different PCMs differ in the phase change temperature and the heat storage capacities. Poly(ethylene glycol) (PEG) was cross-linked to hydroxyl-terminated poly(dimethyl siloxane) (PDMS) in the presence of cross-linker, tetraethyl orthosilicate (TEOS) and catalyst, dibutyltin dilaurate. Four different ratios of PEG and PDMS were reacted together, and the composition with the lowest PEG concentration resulted in the formation of a flexible solid-solid phase change membrane. The other compositions are obtained in powder form. The enthalpy values of the prepared PCMs were studied by using differential scanning calorimetry and the crystallization properties were analyzed by using X-ray diffraction and polarized optical microscopy. The incorporation of silicone moiety was expected to reduce the hydrophilic character of PEG, which was evaluated by measurement of contact angle. The membrane forming ability of this crosslinked polymer can be extended to several smart packaging, building and textile applications. The detailed synthesis, characterization and performance evaluation of the crosslinked polymer blend will be incorporated in the presentation.

Keywords: phase change materials, poly(ethylene glycol), poly(dimethyl siloxane), thermal energy storage

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Authors: Ines Elouedi, Atef Hammouda

Abstract:

This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain.

Keywords: fast generalized multi-directional Radon transform, curve, exact reconstruction, pattern recognition

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Authors: Lattari Samir

Abstract:

The performance of a production process is the result of proper operation where the management tools appear as the key to success through process management which consists of managing and implementing a quality policy, organizing and planning the manufacturing, and thus defining an efficient logic as the main areas covered by production management. To carry out this delicate mission, which requires reconciling often contradictory objectives, the auditor is called upon, who must be able to express an opinion on the effectiveness of the operation of the "production" function. To do this, the auditor must structure his mission in three phases, namely, the preparation phase to assimilate the particularities of this function, the implementation phase and the conclusion phase. The audit is a systematic and independent examination of all the stages of a manufacturing process intended to determine whether the pre-established arrangements for the combination of production factors are respected, whether their implementation is effective and whether they are relevant in relation to the goals.

Keywords: audit, performance of process, independent examination, management tools, audit of accounts

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Authors: R. Faiez, M. Mashhoudi, F. Najafi

Abstract:

Implicit in most large-scale numerical analyses of the crystal growth from the melt is the assumption that the shape and position of the phase boundary are determined by the transport phenomena coupled strongly to the melt hydrodynamics. In the present numerical study, the interface shape-effect on the convective interactions in a Czochralski oxide melt is described. It was demonstrated that thermos-capillary flow affects inversely the phase boundaries of distinct shapes. The in homogenity of heat flux and the location of the stagnation point at the crystallization front were investigated. The forced convection effect on the point displacement at the boundary found to be much stronger for the flat plate interface compared to the cone-shaped one with and without the Marangoni flow.

Keywords: computer simulation, fluid flow, interface shape, thermos-capillary effect

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Authors: Gülay Dalgıç, Gildis Tachir

Abstract:

Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

Procedia PDF Downloads 126