Search results for: silicon transformer modeling with polynomial

Authors: S. Maleczek, K. Drabczyk, L. Bogdan, A. Iwan

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It is known that for industrial applications using solar panel constructed from silicon solar cells require high-efficiency performance. One of the main problems in solar panels is different mechanical and structural defects, causing the decrease of generated power. To analyse defects in solar cells, various techniques are used. However, the thermal imaging is fast and simple method for locating defects. The main goal of this work was to analyze defects in constructed flexible silicon photovoltaic modules via thermal imaging and electroluminescence method. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. Thermal behavior was observed using thermographic camera (VIGOcam v50, VIGO System S.A, Poland) using a DC conventional source. Electroluminescence was observed by Steinbeis Center Photovoltaics (Stuttgart, Germany) equipped with a camera, in which there is a Si-CCD, 16 Mpix detector Kodak KAF-16803type. The camera has a typical spectral response in the range 350 - 1100 nm with a maximum QE of 60 % at 550 nm. In our work commercial silicon solar cells with the size 156 × 156 mm were cut for nine parts (called single solar cells) and used to create photovoltaic modules with the size of 160 × 70 cm (containing about 80 single solar cells). Flexible silicon photovoltaic modules on polyamides or polyester fabric were constructed and investigated taking into consideration anomalies on the surface of modules. Thermal imaging provided evidence of visible voltage-activated conduction. In electro-luminescence images, two regions are noticeable: darker, where solar cell is inactive and brighter corresponding with correctly working photovoltaic cells. The electroluminescence method is non-destructive and gives greater resolution of images thereby allowing a more precise evaluation of microcracks of solar cell after lamination process. Our study showed good correlations between defects observed by thermal imaging and electroluminescence. Finally, we can conclude that the thermographic examination of large scale photovoltaic modules allows us the fast, simple and inexpensive localization of defects at the single solar cells and modules. Moreover, thermographic camera was also useful to detection electrical interconnection between single solar cells.

Keywords: electro-luminescence, flexible devices, silicon solar cells, thermal imaging

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Authors: Tze Jin Wong, Lee Feng Koo, Pang Hung Yiu

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Lenstra’s attack uses Chinese remainder theorem as a tool and requires a faulty signature to be successful. This paper reports on the security responses of fourth and sixth order Lucas based (LUC_4,6) cryptosystem under the Lenstra’s attack as compared to the other two Lucas based cryptosystems such as LUC and LUC₃ cryptosystems. All the Lucas based cryptosystems were exposed mathematically to the Lenstra’s attack using Chinese Remainder Theorem and Dickson polynomial. Result shows that the possibility for successful Lenstra’s attack is less against LUC_4,6 cryptosystem than LUC₃ and LUC cryptosystems. Current study concludes that LUC_4,6 cryptosystem is more secure than LUC and LUC₃ cryptosystems in sustaining against Lenstra’s attack.

Keywords: Lucas sequence, Dickson polynomial, faulty signature, corresponding signature, congruence

Procedia PDF Downloads 158

Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.

Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

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A process that utilizes a combination of additive manufacturing (AM), a preceramic polymer, and a chopped carbon fiber precursorto fabricate Silicon Carbon/ Carbon fibers (SiC/C) composites have been developed. The study has shown a promising, cost-effective, and efficient route to fabricate complex SiC/C composites using additive manufacturing. A key part of this effort was the mapping of the material’s microstructure through the thickness of the composite. Microstructural features in the pyrolyzed composites through the successive AM layers, such as defects, crystal size and their distribution, interatomic spacing, chemical bonds, were investigated using high-resolution scanning and transmission electron microscopy. As a result, the microstructure developed in SiC/C composites after printing, cure, and pyrolysis has been successfully mapped through the thickness of the derived composites. Dense and nearly defect-free parts after polymer to ceramic conversion were observed. The ceramic matrix composite displayed three coexisting phases, including silicon carbide, silicon oxycarbide, and turbostratic carbon. Lattice fringes imaging and X-Ray Diffraction analysis showed well-defined SiC and turbostratic carbon features. The cross-sectional mapping of the printed-then-pyrolyzed structures has confirmed consistent structural and chemical features within the internal layers of the AM parts. Noteworthy, however, is that a crust-like area with high crystallinity has been observed in the first and last external layers. Not only do these crust-like regions have structural characteristics distinct from the internal layers, but they also have elemental distributions different than the internal layers.

Keywords: SiC, preceramic polymer, additive manufacturing, ceramic

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Fatima Zohra Rahou, A. Guen Bouazza, B. Bouazza

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Invention of transistor is the foundation of electronics industry. Metal Oxide Semiconductor Field Effect Transistor (MOSFET) has been the key for the development of nanoelectronics technology. In the first part of this manuscript, we present a new generation of MOSFET transistors based on SOI (Silicon-On-Insulator) technology. It is a partially depleted Silicon-On-Insulator (PD SOI MOSFET) transistor simulated by using SILVACO software. This work was completed by the presentation of some results concerning the influence of parameters variation (channel length L and gate oxide thickness Tox) on our PDSOI n-MOSFET structure on its drain current and kink effect.

Keywords: SOI technology, PDSOI MOSFET, FDSOI MOSFET, kink effect

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Authors: Derkaoui Orkia, Lehireche Ahmed

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The topic of this article is to exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for solving NP-hard problems. This approach provides tight relaxations of combinatorial and quadratic problems. In this work, we solve the maximum clique problem using this relaxation. The clique problem is the computational problem of finding cliques in a graph. It is widely acknowledged for its many applications in real-world problems. The numerical results show that it is possible to find a maximum clique in polynomial time, using an algorithm based on semidefinite programming. We implement a primal-dual interior points algorithm to solve this problem based on semidefinite programming. The semidefinite relaxation of this problem can be solved in polynomial time.

Keywords: semidefinite programming, maximum clique problem, primal-dual interior point method, relaxation

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Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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Authors: Ilija Plecas, Dalibor Arbutina

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The leaching rate of 60Co from spent mix bead (anion and cation) exchange resins in a cement-bentonite matrix has been studied. Transport phenomena involved in the leaching of a radioactive material from a cement-bentonite matrix are investigated using three methods based on theoretical equations. These are: the diffusion equation for a plane source, an equation for diffusion coupled to a first order equation and an empirical method employing a polynomial equation. The results presented in this paper are from a 25-year mortar and concrete testing project that will influence the design choices for radioactive waste packaging for a future Serbian radioactive waste disposal center.

Keywords: cement, concrete, immobilization, leaching, permeability, radioactivity, waste

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Authors: Sefiu A. Bello, Nasirudeen K. Raji, Jeleel A. Adebisi, Sadiq A. Raji

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Pure metals are not used in most cases for structural applications because of their limited properties. Presently, high entropy alloys (HEAs) are emerging by mixing comparative proportions of metals with the aim of maximizing the entropy leading to enhancement in structural and mechanical properties. Aluminum Silicon Nickel Iron Vanadium (AlSiNiFeV) alloy was developed using stir cast technique and analysed. Results obtained show that the alloy grade G0 contains 44 percentage by weight (wt%) Al, 32 wt% Si, 9 wt% Ni, 4 wt% Fe, 3 wt% V and 8 wt% for minor elements with tensile strength and elongation of 106 Nmm^-2 and 2.68%, respectively. X-ray diffraction confirmed intermetallic compounds having hexagonal closed packed (HCP), orthorhombic and cubic structures in cubic dendritic matrix. This affirmed transformation from the cubic structures of elemental constituents of the HEAs to the precipitated structures of the intermetallic compounds. A maximum tensile strength of 188 Nmm^-2 with 4% elongation was noticed at 10wt% of silica addition to the G0. An increase in tensile strength with an increment in silica content could be attributed to different phases and crystal geometries characterizing each HEA.

Keywords: HEAs, phases model, aluminium, silicon, tensile strength, model

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Authors: Karima Benfadel, Lamia Talbi, Sabiha Anas Boussaa, Afaf Brik, Assia Boukezzata, Yahia Ouadah, Samira Kaci

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In order to prevent global warming, which is mainly caused by the increase in carbon dioxide levels in the atmosphere, it is interesting to produce renewable energy in the form of chemical energy by converting carbon dioxide into alternative fuels and other energy-dense products. Photoelectrochemical reduction of carbon dioxide to value-added products and fuels is a promising and current method. The objective of our study is to develop Cu₂S-based photoélectrodes, in which Cu₂S is used as a CO₂ photoelectrocatalyst deposited on nanostructured silicon substrates. Cu₂S thin layers were deposited using the chemical bath deposition (CBD) technique. Silicon nanowires and nanopyramids were obtained by alkaline etching. SEM and UV-visible spectroscopy was used to analyse the morphology and optical characteristics. By using a potentiostat station, we characterized the photoelectrochemical properties. We performed cyclic voltammetry in the presence and without CO₂ purging as well as linear voltammetry (LSV) in the dark and under white light irradiation. We perform chronoamperometry to study the stability of our photocathodes. The quality of the nanowires and nanopyramids was visible in the SEM images, and after Cu₂S deposition, we could see how the deposition was distributed over the textured surfaces. The inclusion of the Cu₂S layer applied on textured substrates significantly reduces the reflectance (R%). The catalytic performance towards CO₂ conversion of Cu₂S/Si-based photocathodes revealed that the texturing of the silicon surface with nanowires and pyramids has a better photoelectrochemical behavior than those without surface modifications.

Keywords: CO₂ conversion, Cu₂S photocathode, silicone nanostructured, electrochemistry

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Authors: Rahul Ganpat Mapari, D. G. Wakde

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In this paper, a proposed approach to improve the power factor of single-phase rectifiers and to regulate the output voltage against the change in grid voltage and load is presented. This converter topology is evaluated on the basis of performance and its salient features like simplicity, low cost and high performance are discussed to analyze its applicability. The proposed control strategy is bridgeless, transformer-less and output current sensor-less and consists of only two Bi-directional IGBTs and two diodes. The voltage regulation is achieved by a simple voltage divider to communicate to a controller to control the duty cycles of PWM. A control technique and operational procedure are also developed, both theoretically and experimentally. The experimental results clearly verify the theoretical analysis from the prototype connected to grid unity.

Keywords: Active Rectifier (AC-DC), power factor, single phase, voltage regulation

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Authors: Zoltan Theisz, Gergely Mezei

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Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead

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Authors: Yasser Ahmed Mahmoud Ali Helal

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The use of CAD (Computer Aided Design) technology is ubiquitous in the architecture, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of architecture schools in Nigeria as an important part of the training module. This article examines the ethical issues involved in implementing CAD (Computer Aided Design) content into the architectural education curriculum. Using existing literature, this study begins with the benefits of integrating CAD into architectural education and the responsibilities of different stakeholders in the implementation process. It also examines issues related to the negative use of information technology and the perceived negative impact of CAD use on design creativity. Using a survey method, data from the architecture department of University was collected to serve as a case study on how the issues raised were being addressed. The article draws conclusions on what ensures successful ethical implementation. Millions of people around the world suffer from hepatitis C, one of the world's deadliest diseases. Interferon (IFN) is treatment options for patients with hepatitis C, but these treatments have their side effects. Our research focused on developing an oral small molecule drug that targets hepatitis C virus (HCV) proteins and has fewer side effects. Our current study aims to develop a drug based on a small molecule antiviral drug specific for the hepatitis C virus (HCV). Drug development using laboratory experiments is not only expensive, but also time-consuming to conduct these experiments. Instead, in this in silicon study, we used computational techniques to propose a specific antiviral drug for the protein domains of found in the hepatitis C virus. This study used homology modeling and abs initio modeling to generate the 3D structure of the proteins, then identifying pockets in the proteins. Acceptable lagans for pocket drugs have been developed using the de novo drug design method. Pocket geometry is taken into account when designing ligands. Among the various lagans generated, a new specific for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Mauludi Ariesto Pamungkas, Wafa Maftuhin

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Gallium with three outer electrons commonly are used as dopants of silicon to make it P type and N type semiconductor respectively. Silicene, one-atom-thick silicon layer is one of emerging two dimension materials after the success of graphene. The effects of Gallium doping on electronic structure of silicine are investigated by using first principle calculation based on Density Functional Theory (DFT) calculation and norm conserving pseudopotential method implemented in ABINIT code. Bandstructure of Pristine silicene is similar to that of graphene. Effect of Ga doping on bandstructure of silicene depend on the position of Ga adatom on silicene

Keywords: silicene, effects of Gallium doping, Density Functional Theory (DFT), graphene

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Authors: Malika Yaici, Kamel Hariche, Tim Clarke

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The relationship between eigenstructure (eigenvalues and eigenvectors) and latent structure (latent roots and latent vectors) is established. In control theory eigenstructure is associated with the state space description of a dynamic multi-variable system and a latent structure is associated with its matrix fraction description. Beginning with block controller and block observer state space forms and moving on to any general state space form, we develop the identities that relate eigenvectors and latent vectors in either direction. Numerical examples illustrate this result. A brief discussion of the potential of these identities in linear control system design follows. Additionally, we present a consequent result: a quick and easy method to solve the polynomial eigenvalue problem for regular matrix polynomials.

Keywords: eigenvalues/eigenvectors, latent values/vectors, matrix fraction description, state space description

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Authors: Peter Edwar Mortada Nasif

Abstract:

The use of CAD (Computer Aided Design) technology is ubiquitous in the architecture, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of architecture schools in Nigeria as an important part of the training module. This article examines the ethical issues involved in implementing CAD (Computer Aided Design) content into the architectural education curriculum. Using existing literature, this study begins with the benefits of integrating CAD into architectural education and the responsibilities of different stakeholders in the implementation process. It also examines issues related to the negative use of information technology and the perceived negative impact of CAD use on design creativity. Using a survey method, data from the architecture department of Chukwuemeka Odumegwu Ojukwu Uli University was collected to serve as a case study on how the issues raised were being addressed. The article draws conclusions on what ensures successful ethical implementation. Millions of people around the world suffer from hepatitis C, one of the world's deadliest diseases. Interferon (IFN) is treatment options for patients with hepatitis C, but these treatments have their side effects. Our research focused on developing an oral small molecule drug that targets hepatitis C virus (HCV) proteins and has fewer side effects. Our current study aims to develop a drug based on a small molecule antiviral drug specific for the hepatitis C virus (HCV). Drug development using laboratory experiments is not only expensive, but also time-consuming to conduct these experiments. Instead, in this in silicon study, we used computational techniques to propose a specific antiviral drug for the protein domains of found in the hepatitis C virus. This study used homology modeling and abs initio modeling to generate the 3D structure of the proteins, then identifying pockets in the proteins. Acceptable lagans for pocket drugs have been developed using the de novo drug design method. Pocket geometry is taken into account when designing ligands. Among the various lagans generated, a new specific for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, hepatitis C virus, computer aided design, CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models, and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. It is important to design systems based on structural analysis, research, and evaluation of efficiency indicators. One of the important efficiency criteria is the reliability of the system, which depends on the components of the structure. Quantifying the reliability of large-scale systems is a computationally complex process, and it is advisable to perform it with the help of a computer. Logical-probabilistic modeling is one of the effective means of describing the structure of a complex system and quantitatively evaluating its reliability, which was the basis of our application. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of “weights” of elements of system. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research, and designing of optimal structure systems are carried out.

Keywords: complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability of systems, “weights” of elements

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Authors: Jianwen Li, Hongfang Ma, Weixin Qian, Haitao Zhang, Weiyong Ying

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Methanol-to-propylene conversion was carried out in a continuous-flow fixed-bed reactor over nano-sized HZSM-5 zeolites. The HZSM-5 catalysts were synthesized with different Si/Al ratio and silicon sources, and treated with NaOH. The structural property, morphology, and acidity of catalysts were measured by XRD, N₂ adsorption, FE-SEM, TEM, and NH₃-TPD. The results indicate that the increment of Si/Al ratio decreased the acidity of catalysts and then improved propylene selectivity, while silicon sources had slight impact on the acidity but affected the product distribution. The desilication after alkali treatment could increase intracrystalline mesopores and enhance propylene selectivity.

Keywords: alkali treatment, HZSM-5, methanol-to-propylene, synthesis condition

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Authors: Masoud Safarishaal

Abstract:

Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

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Authors: Amanbek Jainakov, Abdikerim Kurbanaliev

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The work presents the results of mathematical modeling of large-scale flows in areas with a complex topographic relief. The Reynolds-averaged Navier—Stokes equations constitute the basis of the three-dimensional unsteady modeling. The well-known Volume of Fluid method implemented in the solver interFoam of the open package OpenFOAM 2.3 is used to track the free-boundary location. The mathematical model adequacy is checked by comparing with experimental data. The efficiency of the applied technology is illustrated by the example of modeling the breakthrough of the dams of the Andijan (Uzbekistan) and Papan (near the Osh town, Kyrgyzstan) reservoir.

Keywords: three-dimensional modeling, free boundary, the volume-of-fluid method, dam break, flood, OpenFOAM

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Ming-Kwei Lee, Chih-Feng Yen

Abstract:

The electrical characteristics of liquid phase deposited silicon oxynitride film on ammonium sulfide treated p-type (100) gallium arsenide substrate were investigated. Hydrofluosilicic acid, ammonia and boric acid aqueous solutions were used as precursors. The electrical characteristics of silicon oxynitride film are much improved on gallium arsenide substrate with ammonium sulfide treatment. With post-metallization annealing, hydrogen ions can further passivate defects in SiON/GaAs film and interface. The leakage currents can reach 7.1 × 10-8 and 1.8 × 10-7 at ± 2 V. The dielectric constant and effective oxide charges are 5.6 and -5.3 × 1010 C/cm2, respectively. The hysteresis offset of hysteresis loop is merely 0.09 V.

Keywords: liquid phase deposition, SiON, GaAs, PMA, (NH4)2S

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Authors: Mohammad Farooq Wani

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Tribological studies on nano-sized ß-silicon nitride+5% BN were carried out in dry air at high temperatures to clarify the lack of consensus in the bibliographic data concerning the Tribological behavior of Si3N4 ceramics and effect of doped hexagonal boron nitride on coefficient of friction and wear coefficient at different loads and elevated temperatures. The composites were prepared via high energy mechanical milling and subsequent spark plasma sintering using Y2O3 and Al2O3 as sintering additives. After sintering, the average crystalline size of Si3N4 was observed to be 50 nm. Tribological tests were performed with temperature and Friction coefficients 0.16 to 1.183 and 0.54 to 0.71 were observed for Nano-sized ß-silicon nitride+5% BN composite under normal load of 10N-70 N and over high temperature range of 350 ºC-550 ºC respectively. Specific wear coefficients from 1.33x 10-4 mm3N-1m-1 to 4.42x 10-4 mm3N-1m-1 were observed for Nano-sized Si3N4 + 5% BN composite against Si3N4 ball as tribo-pair counterpart over high temperature range of 350 ºC-550 ºC while as under normal load of 10N to70N Specific wear coefficients of 6.91x 10-4 mm3N-1m-1 to 1.70x 10-4 were observed. The addition of BN to the Si3N4 composite resulted in a slight reduction of the friction coefficient and lower values of wear coefficient.

Keywords: ceramics, tribology, friction and wear, solid lubrication

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Authors: Mario Hanna Louis Hanna

Abstract:

The use of CAD (pc Aided layout) generation is ubiquitous inside the structure, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of structure faculties in Nigeria as an important part of the training module. This newsletter examines the moral troubles involved in implementing CAD (pc Aided layout) content into the architectural training curriculum. Using current literature, this study begins with the advantages of integrating CAD into architectural education and the responsibilities of various stakeholders in the implementation process. It also examines issues related to the terrible use of records generation and the perceived bad effect of CAD use on design creativity. The use of a survey technique, information from the architecture department of Chukwuemeka Odumegwu Ojukwu Uli college changed into accumulated to serve as a case observe on how the problems raised have been being addressed. The object draws conclusions on what guarantees a hit moral implementation. Tens of millions of human beings around the sector suffer from hepatitis C, one of the international's deadliest sicknesses. Interferon (IFN) is a remedy alternative for patients with hepatitis C, but these treatments have their aspect outcomes. Our research targeted growing an oral small molecule drug that goals hepatitis C virus (HCV) proteins and has fewer facet effects. Our contemporary study targets to broaden a drug primarily based on a small molecule antiviral drug precise for the hepatitis C virus (HCV). Drug improvement and the use of laboratory experiments isn't always best high-priced, however also time-eating to behavior those experiments. instead, on this in silicon have a look at, we used computational strategies to recommend a particular antiviral drug for the protein domain names of discovered in the hepatitis C virus. This examines used homology modeling and abs initio modeling to generate the 3-D shape of the proteins, then figuring out pockets within the proteins. Proper lagans for pocket pills were advanced the usage of the de novo drug design method. Pocket geometry is taken into consideration while designing ligands. A few of the various lagans generated, a different for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, Hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication.

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Authors: Wenya Shu, Ilinca Stanciulescu

Abstract:

Carbon nanotubes (CNTs) possess attractive properties, such as high stiffness and strength, and high thermal and electrical conductivities, making them promising filler in multifunctional nanocomposites. Although CNTs can be efficient reinforcements, the expected level of mechanical performance of CNT-polymers is not often reached in practice due to the poor mechanical behavior of the CNT-polymer interfaces. It is believed that the interactions of CNT and polymer mainly result from the Van der Waals force. The interface debonding is a fracture and delamination phenomenon. Thus, the cohesive zone modeling (CZM) is deemed to give good capture of the interface behavior. The detailed, cohesive zone modeling provides an option to consider the CNT-matrix interactions, but brings difficulties in mesh generation and also leads to high computational costs. Homogenized models that smear the fibers in the ground matrix and treat the material as homogeneous are studied in many researches to simplify simulations. But based on the perfect interface assumption, the traditional homogenized model obtained by mixing rules severely overestimates the stiffness of the composite, even comparing with the result of the CZM with artificially very strong interface. A mechanical model that can take into account the interface debonding and achieve comparable accuracy to the CZM is thus essential. The present study first investigates the CNT-matrix interactions by employing cohesive zone modeling. Three different coupled CZM laws, i.e., bilinear, exponential and polynomial, are considered. These studies indicate that the shapes of the CZM constitutive laws chosen do not influence significantly the simulations of interface debonding. Assuming a bilinear traction-separation relationship, the debonding process of single CNT in the matrix is divided into three phases and described by differential equations. The analytical solutions corresponding to these phases are derived. A homogenized model is then developed by introducing a parameter characterizing interface sliding into the mixing theory. The proposed mechanical model is implemented in FEAP8.5 as a user material. The accuracy and limitations of the model are discussed through several numerical examples. The CZM simulations in this study reveal important factors in the modeling of CNT-matrix interactions. The analytical solutions and proposed homogenized model provide alternative methods to efficiently investigate the mechanical behaviors of CNT/polymer composites.

Keywords: carbon nanotube, cohesive zone modeling, homogenized model, interface debonding

Procedia PDF Downloads 125

Authors: Saeed Khandan Siar, Stefan Tenbohlen, Christian Breuer, Raphael Lebreton

Abstract:

The goal of this article is to investigate the detailed temperature distribution and the fluid flow of an oil cooled winding of a power transformer by means of computational fluid dynamics (CFD). The experimental setup consists of three passes of a zig-zag cooled disc type winding, in which losses are modeled by heating cartridges in each winding segment. A precise temperature sensor measures the temperature of each turn. The laboratory setup allows the exact control of the boundary conditions, e.g. the oil flow rate and the inlet temperature. Furthermore, a simulation model is solved using the open source computational fluid dynamics solver OpenFOAM and validated with the experimental results. The model utilizes the laminar and turbulent flow for the different mass flow rate of the oil. The good agreement of the simulation results with experimental measurements validates the model.

Keywords: CFD, conjugated heat transfer, power transformers, temperature distribution

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Authors: Helena M. Wilhelm, Paulo O. Fernandes, Laís P. Dill, Kethlyn G. Moscon

Abstract:

The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.

Keywords: compatibility, Rancimat, natural ester, vegetable oil

Procedia PDF Downloads 202