Search results for: spice simulation

Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha

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A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: K. Shaji Mon, P. R. John Sreenidhi

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In deep-submicrometer CMOS processes, time-domain resolution of a digital signal is becoming higher than voltage resolution of analog signals. This claim is nowadays pushing toward a new circuit design paradigm in which the traditional analog signal processing is expected to be progressively substituted by the processing of times in the digital domain. Within this novel paradigm, digitally controlled delay lines (DCDL) should play the role of digital-to-analog converters in traditional, analog-intensive, circuits. Digital delay locked loops are highly prevalent in integrated systems.The proposed paper addresses the glitches present in delay circuits along with area,power dissipation and signal integrity.The digitally controlled delay lines(DCDL) under study have been designed in a 90 nm CMOS technology 6 layer metal Copper Strained SiGe Low K Dielectric. Simulation and synthesis results show that the novel circuits exhibit no glitches for dual output coarse DCDL with less power dissipation and consumes less area compared to the glitch free NAND based DCDL.

Keywords: glitch free, NAND-based DCDL, CMOS, deep-submicrometer

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Authors: Rachida Ouysse

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This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

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Authors: Eloise C. Tredenick, Troy W. Farrell, W. Alison Forster, Steven T. P. Psaltis

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The agriculture industry requires improved efficacy of sprays being applied to crops. More efficacious sprays provide many environmental and financial benefits. The plant leaf cuticle is known to be the main barrier to diffusion of agrochemicals within the leaf. The importance of a mathematical model to simulate uptake of agrochemicals in plant cuticles has been noted, as the results of each uptake experiments are specific to each formulation of active ingredient and plant species. In this work we develop a mathematical model and numerical simulation for the uptake of ionic agrochemicals through aqueous pores in plant cuticles. We propose a nonlinear porous diffusion model of ionic agrochemicals in isolated cuticles, which provides additions to a simple diffusion model through the incorporation of parameters capable of simulating plant species' variations, evaporation of surface droplet solutions and swelling of the aqueous pores with water. The model could feasibly be adapted to other ionic active ingredients diffusing through other plant species' cuticles. We validate our theoretical results against appropriate experimental data, discuss the key sensitivities in the model and relate theoretical predictions to appropriate physical mechanisms.

Keywords: aqueous pores, ionic active ingredient, mathematical model, plant cuticle, porous diffusion

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Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: Shreyansh Bharadwaj, Raghavendra Kollipara, Sijoy C. D., R. K. Mittal

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Utilizing the Lorentz force to propel an electrically conductive plunger through a solenoid represents a fundamental application in electromagnetism. The parameters of the solenoid significantly influence the force exerted on the plunger, impacting its response. A parametric study has been done to understand the effect of these parameters on the force acting on the plunger. This study is done to determine the most optimal combination of parameters to obtain the fast response. Analysis has been carried out using an algorithm capable of simulating the scenario of a plunger undergoing acceleration within a solenoid. Authors have conducted an analysis focusing on several key configuration parameters of the solenoid. These parameters include the inter-layer gap (in the case of a multi-turn solenoid), different conductor diameters, varying numbers of turns, and diverse numbers of layers. Primary objective of this paper is to discern how alterations in these parameters affect the force applied to the plunger. Through extensive numerical simulations, a dataset has been generated and utilized to construct informative plots. These plots provide visual representations of the relationships between the solenoid configuration parameters and the resulting force exerted on the plunger, which can further be used to deduce scaling laws. This research endeavors to offer valuable insights into optimizing solenoid configurations for enhanced electromagnetic acceleration, thereby contributing to advancements in electromagnetic propulsion technology.

Keywords: Lorentz force, solenoid configuration, electromagnetic acceleration, parametric analysis, simulation

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Authors: A. Khan, H. Mahmood

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In Underwater Wireless Sensor Networks (UWSNs), sensor nodes close to water surface (final destination) are often preferred for selection as forwarders. However, their frequent selection makes them depleted of their limited battery power. In consequence, these nodes die during early stage of network operation and create energy holes where forwarders are not available for packets forwarding. These holes severely affect network throughput. As a result, system performance significantly degrades. In this paper, a routing protocol is proposed to avoid energy holes during packets forwarding. The proposed protocol does not require the conventional position information (localization) of holes to avoid them. Localization is cumbersome; energy is inefficient and difficult to achieve in underwater environment where sensor nodes change their positions with water currents. Forwarders with the lowest water pressure level and the maximum number of neighbors are preferred to forward packets. These two parameters together minimize packet drop by following the paths where maximum forwarders are available. To avoid interference along the paths with the maximum forwarders, a packet holding time is defined for each forwarder. Simulation results reveal superior performance of the proposed scheme than the counterpart technique.

Keywords: energy holes, interference, routing, underwater

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Authors: Maryam Kalkatechi

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Nowadays, parametric design, scientific analysis, and digital fabrication are dominant. Many architectural practices are increasingly seeking to incorporate advanced digital software and fabrication in their projects. Proposing an erudite design process that combines digital and practical aspects in a strong frame within the method was resulted from the dissertation research. The digital aspects are the progressive advancements in algorithm design and simulation software. These aspects have assisted the firms to develop more holistic concepts at the early stage and maintain collaboration among disciplines during the design process. The erudite design process enhances the current design processes by encouraging the designer to implement the construction and architecture knowledge within the algorithm to make successful design processes. The erudite design process also involves the ongoing improvements of applying the new method of 3D printing in construction. This is achieved through the ‘data-sketches’. The term ‘data-sketch’ was developed by the author in the dissertation that was recently completed. It accommodates the decisions of the architect on the algorithm. This paper introduces the erudite design process and its components. It will summarize the application of this process in development of the ‘3D printed construction unit’. This paper contributes to overlaying the academic and practice with advanced technology by presenting a design process that transfers the dominance of tool to the learned architect and encourages innovation in design processes.

Keywords: erudite, data-sketch, algorithm design in architecture, design process

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

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Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Adam Ahmed Hosney

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The existence of a culture of corruption within an institution, such as the police, could be a sign of failure from various angles. There is a general perception among Ghanaians that the most corrupt institution is the police service. The purpose of this study is to formulate and analyze a nonlinear mathematical model to investigate corruption as an epidemic within the Ghana police service, this study revealed the basic reproduction number for corruption extinction and corruption survival. The threshold conditions for all kinds of equilibrium points are obtained using linearization methods and Lyapunov functional methods, and they demonstrate local asymptotic stability for both corrupt endemic and corrupt free equilibrium states. The model was analyzed qualitatively, and the solution was derived. The model appears to be positively invariant and attractive. Therefore, the region exhibits positive invariance. Thus, it is adequate to think about the dynamics of the model. For the purpose of illustrating the solution, the graphic result was presented and discussed. Results show that corruption will die out within the police service if the government shows no tolerance for those involved in corrupt practices. Study findings indicate that leaders should be trustworthy, demonstrate a complete and viable commitment to addressing corruption, and make it a priority to provide mass education to all citizens as well as using religious leaders to fight corruption since most Ghanaians are religious and trust their leaders.

Keywords: mathematical model, differential equation, dynamical system, simulation

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Avram Irina, Coiciu Eugenia-Mihaela, Popovici Mara-Georgiana, Mitu Iani Octavian

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ELI-NP stands as a cutting-edge facility globally, hosting unique radiological setups. It conducts experiments leveraging high-power lasers capable of producing extremely brief 10 PW pulses on two fronts. Moreover, it houses an exceptional gamma beam system with distinctive spectral characteristics. The facility hosts various experiments across designated experimental areas, encompassing ultra-short high-power laser tests, high-intensity gamma beam trials, and combined experiments utilizing both setups. The facility hosts a dosimetry laboratory, which recently obtained accreditation, where the radiation safety group employs a host of different types of detectors for monitoring the personnel, environment, and public exposure to ionizing radiation generated in experiments performed. ELI-NP's design was shaped by radiological protection assessments conducted through Monte Carlo simulations. The poster exemplifies an assessment conducted using the FLUKA code in an experimental area where a high-power laser system is implemented, and the future diagnostic system for variable energy gamma beams will soon be operational.

Keywords: radiation protection, Monte Carlo simulation, FLUKA, dosimetry

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Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all the mechanical properties of fibers, matrix, the fiber/matrix interface, as well as the geometry of the fiber. An appropriate method applicable to the simulation and analysis of toughening is essential. In this work, we performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of the contribution of random fibers to the toughening of composite. Then with numerical programming, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers with high strength and low elasticity modulus benefit toughening; (ii) fibers with relatively high elastic modulus compared to the matrix may result in considerable matrix damage (spalling effect); (iii) employment of high-strength synthetic fiber is a good option. The present work makes it possible to optimize the parameters in order to produce advanced ceramic with desired performance. We believe combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed.

Keywords: bridging stress, discrete element method, fiber reinforced composites, toughening

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Authors: Maninder Kaur Gill, Alpana Agarwal

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It is practically not feasible to measure the open-loop voltage gain of the operational amplifier in the open loop configuration. It is because the open-loop voltage gain of the operational amplifier is very large. In order to avoid the saturation of the output voltage, a very small input should be given to operational amplifier which is not possible to be measured practically by a digital multimeter. A test circuit for measurement of open loop voltage gain of an operational amplifier has been proposed and verified using simulation tools as well as by experimental methods on breadboard. The main advantage of this test circuit is that it is simple, fast, accurate, cost effective, and easy to handle even on a breadboard. The test circuit requires only the device under test (DUT) along with resistors. This circuit has been tested for measurement of open loop voltage gain for different operational amplifiers. The underlying goal is to design testable circuits for various analog devices that are simple to realize in VLSI systems, giving accurate results and without changing the characteristics of the original system. The DUTs used are LM741CN and UA741CP. For LM741CN, the simulated gain and experimentally measured gain (average) are calculated as 89.71 dB and 87.71 dB, respectively. For UA741CP, the simulated gain and experimentally measured gain (average) are calculated as 101.15 dB and 105.15 dB, respectively. These values are found to be close to the datasheet values.

Keywords: Device Under Test (DUT), open loop voltage gain, operational amplifier, test circuit

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Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

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In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

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Authors: Anton Golubkov, Gleb Ermachkov, Aleksandr Smerdin, Oleg Sidorov, Victor Philippov

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Current collection quality is one of the limiting factors when increasing trains movement speed in the rail sector. With the movement speed growth, the impact forces on the current collector from the rolling stock and the aerodynamic influence increase, which leads to the spread in the contact pressure values, separation of the current collector head from the contact wire, contact arcing and excessive wear of the contact elements. The upcoming trend in resolving this issue is the use of the automatic control systems providing stabilization of the contact pressure value. The present paper considers the features of the contemporary automatic control systems of the current collector’s pressure; their major disadvantages have been stated. A scheme of current collector pressure automatic control has been proposed, distinguished by a proactive influence on undesirable effects. A mathematical model of contact strips wearing has been presented, obtained in accordance with the provisions of the central composition rotatable design program. The analysis of the obtained dependencies has been carried out. The procedures for determining the optimal current collector pressure on the contact wire and the pressure control principle in the pneumatic drive have been described.

Keywords: contact strip, current collector, high-speed running, program control, wear

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Authors: Chanh Nghia Nguyen, Yu Kurokawa, Hirotsugu Inoue

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The surface roughness is an important parameter for evaluating the quality of material surfaces since it affects functions and performance of industrial components. Although stylus and optical techniques are commonly used for measuring the surface roughness, they are applicable only to accessible surfaces. In practice, surface roughness measurement from the back side is sometimes demanded, for example, in inspection of safety-critical parts such as inner surface of pipes. However, little attention has been paid to the measurement of back surface roughness so far. Since back surface is usually inaccessible by stylus or optical techniques, ultrasonic technique is one of the most effective among others. In this research, an ultrasonic pulse-echo technique is considered for evaluating the pitch and the height of back surface having periodic triangular profile as a very first step. The pitch of the surface profile is measured by applying the diffraction grating theory for oblique incidence; then the height is evaluated by numerical analysis based on the Kirchhoff theory for normal incidence. The validity of the proposed method was verified by both numerical simulation and experiment. It was confirmed that the pitch is accurately measured in most cases. The height was also evaluated with good accuracy when it is smaller than a half of the pitch because of the approximation in the Kirchhoff theory.

Keywords: back side, inaccessible surface, periodic roughness, pulse-echo technique, ultrasonic NDE

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Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

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Presence of cavities in soil predictably induces ground deformation and changes in soil stress, which might influence adjacent existing pile foundations, though the effect of twin cavities on a nearby pile needs to be understood. This research is an attempt to identify the behaviour of piles subjected to axial load and embedded in cavitied clayey soil. A series of finite element modelling were conducted to investigate the performance of piled foundation located in such soils. The validity of the numerical simulation was evaluated by comparing it with available field test and alternative analytical model. The study involved many parameters such as twin cavities size, depth, spacing between cavities, and eccentricity of cavities from the pile axis on the pile performance subjected to axial load. The study involved many cases; in each case, a critical value has been found in which cavities’ presence has shown minimum impact on the behaviour of pile. Load-displacement relationships of the affecting parameters on the pile behaviour were presented to provide helpful information for designing piled foundation situated near twin underground cavities. It was concluded that the presence of the cavities within the soil mass reduces the ultimate capacity of pile. This reduction differs according to the size and location of the cavity.

Keywords: axial load, clay, finite element, pile, twin cavities, ultimate capacity

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Authors: Sadia Rafiq, Md. Ashab Siddique Zaki, Ananya Roy

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Mountain cycling is a type of off-road bicycle racing that typically takes place on rocky, arid, or other challenging terrains on specially-made mountain cycles. Professional cyclists race while attempting to stay on their bikes in a variety of locales across the world. For safety measures in mountain cycling, as there we have a high chance of injury in case of tire puncture, it’s a preferable way to use an airless tire instead of a pneumatic tire. As airless tire does not tend to go flat, it needs to be replaced less frequently. The airless tire replaces the pneumatic tire, wheel, and tire system with a single unit. It consists of a stiff hub connected to a shear band by flexible, pliable spokes, which is made of poly-composite and a tread band, all of which work together as a single unit to replace all of the components of a normal radial tire. In this paper, an analysis of airless tires in the mountain cycle is shown along with structure and material study. We will be taking the Honeycomb and Diamond Structure of spokes to compare the deformation in both cases and choose our preferable structure. As we know, the tread and spokes deform with the surface roughness and impact. So, the tire tread thickness and the design of spokes can control how much the tire can distort. Through the simulation, we can come to the conclusion that the diamond structure deforms less than the honeycomb structure. So, the diamond structure is more preferable.

Keywords: airless tire, diamond structure, honeycomb structure, deformation

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Farhan Beg

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A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

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Authors: Muhammad Ganda Wiratama

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XYZ company is one of the upstream chemical companies that produce chemical products such as NaOH, HCl, NaClO, VCM, EDC, and PVC for downstream companies. The products are shipped by land using trucks and sea lanes using ship mode. Especially for solid products such as flake caustic soda (F-NaOH) and PVC resin, the products are sold in loose bag packing and palletize packing (packed in pallet). The focus of this study is to increase the number of items that can be loaded in pallet packaging on the company's logistics vehicle. This is very difficult because on this packaging, the dimensions or size of the material to be loaded become larger and certainly much heavier than the loose bag packing. This factor causes the arrangement and handling of materials in the mode of transportation more difficult. In this case, it is difficult to load a different type of volume packing pallet dimension in one truck or container. By using the Cube-IQ software, it is hoped that the planning of stuffing activity material by pallet can become easier in optimizing the existing space with various possible combinations of possibilities. In addition, the output of this software can also be used as a reference for operators in the material handling include the order and orientation of materials contained in the truck or container. The more optimal contents of logistics cargo, then transportation costs can also be minimized.

Keywords: loading activity, container loading, palletize product, simulation

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Authors: R. Kishan, R. M. Sumant, S. Suhas, Arun Mahalingam

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This paper mainly researched on influence of vortex generator on lift coefficient and drag coefficient, when vortex generator is mounted on a flat plate. Vented cylinders were used as vortex generators which intensify vortex shedding in the wake of the vented cylinder as compared to base line circular cylinder which ensures more attached flow and increases lift force of the system. Firstly vented cylinders were analyzed in commercial CFD software which is compared with baseline cylinders for different angles of attack and further variation of lift and drag forces were studied by varying Reynolds number to account for influence of turbulence and boundary layer in the flow. Later vented cylinders were mounted on a flat plate and variation of lift and drag coefficients was studied by varying angles of attack and studying the dependence of Reynolds number and dimensions of vortex generator on the coefficients. Mesh grid sensitivity is studied to check the convergence of the results obtained It was found that usage of vented cylinders as vortex generators increased lift forces with small variation in drag forces by varying angle of attack.

Keywords: CFD analysis, drag coefficient, FVM, lift coefficient, modeling, Reynolds number, simulation, vortex generators, vortex shedding

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Authors: Hanqing Yang, Xiang Meng, Qi Li, Weirong Chen

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The SOC (state of charge) based droop control has limitations on the load power sharing among different energy storage units, due to the line impedance. In this paper, a distributed control strategy for dispersed energy storage units in the DC microgrid based on discrete consensus is proposed. Firstly, a sparse information communication network is built. Thus, local controllers can communicate with its neighbors using voltage, current and SOC information. An average voltage of grid can be evaluated to compensate voltage offset by droop control, and an objective virtual resistance fulfilling above requirement can be dynamically calculated to distribute load power according to the SOC of the energy storage units. Then, the stability of the whole system and influence of communication delay are analyzed. It can be concluded that this control strategy can improve the robustness and flexibility, because of having no center controller. Finally, a model of DC microgrid with dispersed energy storage units and loads is built, the discrete distributed algorithm is established and communication protocol is developed. The co-simulation between Matlab/Simulink and JADE (Java agent development framework) has verified the effectiveness of proposed control strategy.

Keywords: dispersed energy storage units, discrete consensus algorithm, state of charge, communication delay

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Authors: Mohammad A. Sazzad, Md M. Alam

Abstract:

Wind energy is one of the cleanest form of renewable energy. Despite wind industry is growing faster than ever there are some roadblocks towards the improvement. One of the difficulties the industry facing is insufficient knowledge about wake within the wind farms. As we know energy is generated in the lowest layer of the atmospheric boundary layer (ABL). This interaction between the wind turbine (WT) blades and wind introduces a low speed wind region which is defined as wake. This wake region shows different characteristics under each stability condition of the ABL. So, it is fundamental to know this wake region well which is defined mainly by turbulence transport and wake shear. Defining the wake recovery length and width are very crucial for wind farm to optimize the generation and reduce the waste of power to the grid. Therefore, in order to obtain the turbulent coefficients of velocity and length, this research focused on the large eddy simulation (LES) data for neutral ABL (NABL). According to turbulent theory, if we can present velocity defect and Reynolds stress in the form of local length and velocity scales, they become invariant. In our study velocity and length coefficients are 0.4867 and 0.4794 respectively which is close to the theoretical value of 0.5 for NABL. There are some invariant profiles because of the presence of thermal and wind shear power coefficients varied a little from the ideal condition.

Keywords: atmospheric boundary layer, renewable energy, turbulent coefficient, wind turbine, wake

Procedia PDF Downloads 133

Authors: Bouharati Lokman, Bouharati Imen, Bouharati Khaoula, Bouharati Oussama, Bouharati Saddek

Abstract:

Ionizing radiation exposure is an established cancer risk factor. Compared to other common environmental carcinogens, it is relatively easy to determine organ-specific radiation dose and, as a result, radiation dose-response relationships tend to be highly quantified. Nevertheless, there can be considerable uncertainty about questions of radiation-related cancer risk as they apply to risk protection and public policy, and the interpretations of interested parties can differ from one person to another. Examples of tools used in the analysis of the risk of developing cancer due to radiation are characterized by uncertainty. These uncertainties are related to the history of exposure and different assumptions involved in the calculation. We believe that the results of statistical calculations are characterized by uncertainty and imprecision. Having regard to the physiological variation from one person to another. In this study, we develop a tool based on fuzzy logic inference. As fuzzy logic deals with imprecise and uncertain, its application in this area is adequate. We propose a fuzzy system with three input variables (age, sex and body attainable cancer). The output variable expresses the risk of infringement rate of each organ. A base rule is established from recorded actual data. After successful simulation, this will instantly predict the risk of infringement rate of each body following chronic exposure to 0.1 Gy.

Keywords: radiation exposure, cancer, modeling, fuzzy logic

Procedia PDF Downloads 312

Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen

Abstract:

Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.

Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark

Procedia PDF Downloads 351

Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

Abstract:

The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use Microsoft^TM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: aircraft aerodynamic model, total least squares estimation, piloting the aircraft, robust control, Microsoft Flight Simulator, MQ-1 predator

Procedia PDF Downloads 287