Search results for: Current Park’s Vector Modulus (CPVM)

Authors: Jae Kyung Lee, Joon Young Park

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Maintenance on power transmission lines requires a lot of works. Sometimes they should be maintained on live-line environment with high altitude. Therefore, there always exist risks of falling from height and electric shock. To decline those risks, drones are recently applying on the electric power industry. This paper presents new operational technology while inspecting power transmission line. This paper also describes a technique for creating a flight path of a drone for transmission line inspection and a technique for controlling the drones of different types. Its technical and economical feasibilities have confirmed through experiments.

Keywords: drones, transmission line, inspection, control system

Procedia PDF Downloads 338

Authors: Mehrzad Mohabbi Yadollahi, Ramazan Demirboğa, Majid Atashafrazeh

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Geopolymers are highly complex materials which involve many variables which makes modeling its properties very difficult. There is no systematic approach in mix design for Geopolymers. Since the amounts of silica modulus, Na2O content, w/b ratios and curing time have a great influence on the compressive strength an ANFIS (Adaptive neuro fuzzy inference system) method has been established for predicting compressive strength of ground pumice based Geopolymers and the possibilities of ANFIS for predicting the compressive strength has been studied. Consequently, ANFIS can be used for geopolymer compressive strength prediction with acceptable accuracy.

Keywords: geopolymer, ANFIS, compressive strength, mix design

Procedia PDF Downloads 823

Authors: E. Tchandao Mangamana, V. Cariou, E. Vigneau, R. Glele Kakai, E. M. Qannari

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A new definition of a latent variable associated with a dataset makes it possible to propose variants of the PLS2 regression and the multi-block PLS (MB-PLS). We shall refer to these variants as Rd-PLS regression and Rd-MB-PLS respectively because they are inspired by both Redundancy analysis and PLS regression. Usually, a latent variable t associated with a dataset Z is defined as a linear combination of the variables of Z with the constraint that the length of the loading weights vector equals 1. Formally, t=Zw with ‖w‖=1. Denoting by Z' the transpose of Z, we define herein, a latent variable by t=ZZ’q with the constraint that the auxiliary variable q has a norm equal to 1. This new definition of a latent variable entails that, as previously, t is a linear combination of the variables in Z and, in addition, the loading vector w=Z’q is constrained to be a linear combination of the rows of Z. More importantly, t could be interpreted as a kind of projection of the auxiliary variable q onto the space generated by the variables in Z, since it is collinear to the first PLS1 component of q onto Z. Consider the situation in which we aim to predict a dataset Y from another dataset X. These two datasets relate to the same individuals and are assumed to be centered. Let us consider a latent variable u=YY’q to which we associate the variable t= XX’YY’q. Rd-PLS consists in seeking q (and therefore u and t) so that the covariance between t and u is maximum. The solution to this problem is straightforward and consists in setting q to the eigenvector of YY’XX’YY’ associated with the largest eigenvalue. For the determination of higher order components, we deflate X and Y with respect to the latent variable t. Extending Rd-PLS to the context of multi-block data is relatively easy. Starting from a latent variable u=YY’q, we consider its ‘projection’ on the space generated by the variables of each block Xk (k=1, ..., K) namely, tk= XkXk'YY’q. Thereafter, Rd-MB-PLS seeks q in order to maximize the average of the covariances of u with tk (k=1, ..., K). The solution to this problem is given by q, eigenvector of YY’XX’YY’, where X is the dataset obtained by horizontally merging datasets Xk (k=1, ..., K). For the determination of latent variables of order higher than 1, we use a deflation of Y and Xk with respect to the variable t= XX’YY’q. In the same vein, extending Rd-MB-PLS to the path modeling setting is straightforward. Methods are illustrated on the basis of case studies and performance of Rd-PLS and Rd-MB-PLS in terms of prediction is compared to that of PLS2 and MB-PLS.

Keywords: multiblock data analysis, partial least squares regression, path modeling, redundancy analysis

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Authors: A. R. Nezamabadi, M. Veiskarami

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This paper studies free vibration of simply supported functionally graded beams with piezoelectric layers based on the first order shear deformation theory. The Young's modulus of beam is assumed to be graded continuously across the beam thickness. The governing equation is established. Resulting equation is solved using the Euler's equation. The effects of the constituent volume fractions, the influences of applied voltage on the vibration frequency are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: mechanical buckling, functionally graded beam, first order shear deformation theory, free vibration

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Authors: E. Ramprasath, P. Manojkumar, P. Veena

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DC motors have been widely used in the past centuries which are proudly known as the workhorse of industrial systems until the invention of the AC induction motors which makes a huge revolution in industries. Since then, the use of DC machines have been decreased due to enormous factors such as reliability, robustness and complexity but it lost its fame due to the losses. A new methodology is proposed to construct a DC motor through the simulation in LabVIEW to get an idea about its real time performances, if a change in parameter might have bigger improvement in losses and reliability.

Keywords: analysis, characteristics, direct current motor, LabVIEW software, simulation

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Authors: Omer Livvarcin, Mary Kay Park, Michael Miles

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The current literature includes a few studies that mention the impact of relations between teams, the business environment, and experiences from previous projects. There is, however, limited research that treats the phenomenon of project atmosphere (PA) as a whole. This is especially true of research identifying parameters and sub-parameters, which allow project management (PM) teams to build a project culture that ultimately imbues project success. This study’s findings identify a number of key project atmosphere parameters and sub-parameters that affect project management success. One key parameter identified in the study is a cluster related to cultural concurrence, including artifacts such as policies and mores, values, perceptions, and assumptions. A second cluster centers on motivational concurrence, including such elements as project goals and team-member expectations, moods, morale, motivation, and organizational support. A third parameter cluster relates to experiential concurrence, with a focus on project and organizational memory, previous internal PM experience, and external environmental PM history and experience). A final cluster of parameters is comprised of those falling in the area of relational concurrence, including inter/intragroup relationships, role conflicts, and trust. International and intercultural project management data was collected and analyzed from the following countries: Canada, China, Nigeria, South Korea and Turkey. The cross-cultural nature of the data set suggests increased confidence that the findings will be generalizable across cultures and thus applicable for future international project management success. The intent of the identification of project atmosphere as a critical project management element is that a clear understanding of the dynamics of its sub-parameters upon projects may significantly improve the odds of success of future international and intercultural projects.

Keywords: project management, project atmosphere, cultural concurrence, motivational concurrence, relational concurrence

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Authors: Robert Setekera, Ramses van der Toorn

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We present an extensive analysis of the temperature dependence of the local avalanche model used in most of the modern compact models for bipolar transistors. This local avalanche model uses the Chynoweth's empirical law for ionization coefficient to define the generation of the avalanche current in terms of the local electric field. We carry out the model analysis using DC-measurements taken on both Si and advanced SiGe bipolar transistors. For the advanced industrial SiGe-HBTs, we consider both high-speed and high-power devices (both NPN and PNP transistors). The limitations of the local avalanche model in modeling the temperature dependence of the avalanche current mostly in the weak avalanche region are demonstrated. In addition, the model avalanche parameters are analyzed to see if they are in agreement with semiconductor device physics.

Keywords: avalanche multiplication, avalanche current, bipolar transistors, compact modeling, electric field, impact ionization, local avalanche

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Authors: Mustapha Kamel Mihoubi, Hocine Dahmani

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Over recent years much progress has been achieved in the fields of numerical modeling shoreline processes: waves, currents, waves and current. However, there are still some problems in the existing models to link the on the first, the hydrodynamics of waves and currents and secondly, the sediment transport processes and due to the variability in time, space and interaction and the simultaneous action of wave-current near the shore. This paper is the establishment of a numerical modeling to forecast the sediment transport from development scenarios of harbor structure. It is established on the basis of a numerical simulation of a water-sediment model via a 2D model using a set of codes calculation MIKE 21-DHI software. This is to examine the effect of the sediment transport drivers following the dominant incident wave in the direction to pass input harbor work under different variants planning studies to find the technical and economic limitations to the sediment transport and protection of the harbor structure optimum solution.

Keywords: swell, current, radiation, stress, mesh, mike21, sediment

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Authors: R. Saini, R. Lal

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The effect of non-homogeneity on the free transverse vibration of thin rectangular plates of bilinearly varying thickness has been analyzed using generalized differential quadrature (GDQ) method. The non-homogeneity of the plate material is assumed to arise due to linear variations in Young’s modulus and density of the plate material with the in-plane coordinates x and y. Numerical results have been computed for fully clamped and fully simply supported boundary conditions. The solution procedure by means of GDQ method has been implemented in a MATLAB code. The effect of various plate parameters has been investigated for the first three modes of vibration. A comparison of results with those available in literature has been presented.

Keywords: rectangular, non-homogeneous, bilinear thickness, generalized differential quadrature (GDQ)

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Authors: Koichi Kurita

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In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

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Authors: Chao-Qing Dai

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Two families of exact travelling solutions for the discrete sine-Gordon equation are constructed based on the variable-coefficient Jacobian elliptic function method and different transformations. When the modulus of Jacobian elliptic function solutions tends to 1, soliton solutions can be obtained. Some soliton solutions degenerate into the known solutions in literatures. Moreover, dynamical properties of exact solutions are investigated. Our analysis and results may have potential values for certain applications in modern nonlinear science and textile engineering.

Keywords: exact solutions, variable-coefficient Jacobian elliptic function method, discrete sine-Gordon equation, dynamical behaviors

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Authors: Shinta Holdsworth, Jan Axmacher, Darren J. Mann

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Beetles represent the most diverse insect taxon, and they contribute significantly to a wide range of vital ecological functions. Examples include decomposition by bark beetles, nitrogen recycling and dung processing by dung beetles or pest control by predatory ground beetles. Nonetheless, research into the distribution patterns, species richness and functional diversity of beetles particularly from tropical regions remains extremely limited. In our research, we aim to investigate the distribution and diversity patterns of beetles and the roles they play in small tropical island ecosystems in the Kepulauan Seribu Marine National Park and on Java. Our research furthermore provides insights into the effects anthropogenic activities have on the assemblage composition and diversity of beetles on the small islands. We recorded a substantial number of highly abundant small island species, including a substantial number of unique small island species across the study area, highlighting these islands’ potential importance for the regional conservation of genetic resources. The highly varied patterns observed in relation to the use of different trapping types - pitfall traps and flight interception traps (FITs) - underscores the need for complementary trapping strategies that combine multiple methods for beetle community surveys in tropical islands. The significant impacts of human activities have on the small island beetle faunas were also highlighted in our research. More island beetle species encountered in settlement than forest areas shows clear trend of positive links between anthropogenic activities and the overall beetle species richness. However, undisturbed forests harboured a high number of unique species, also in comparison to disturbed forests. Finally, our study suggests that, with regards to different feeding guilds, the diversity of herbivorous beetles on islands is strongly affected by the different levels of forest cover encountered.

Keywords: beetle diversity, forest disturbance, island biogeography, island settlement

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Authors: G. P. Abdel Rahim, M. María Guadalupe Moreno Armenta, Jairo Arbey Rodriguez

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We investigated the structure and electronic properties of the compound Mg1-xBixO with varying concentrations of 0, ¼, ½, and ¾ x bismuth in the the NaCl (rock-salt) and WZ (wurtzite) phases. The calculations were performed using the first-principles pseudo-potential method within the framework of spin density functional theory (DFT). Our calculations predict that for Bi concentrations greater than ~70%, the WZ structure is more favorable than the NaCl one and that for x = 0 (pure MgO), x = 0.25 and x = 0.50 of Bi concentration the NaCl structure is more favorable than the WZ one. For x = 0.75 of Bi, a transition from wurtzite towards NaCl is possible, when the pressure is about 22 GPa. Also It has been observed the crystal lattice constant closely follows Vegard’s law, that the bulk modulus and the cohesion energy decrease with the concentration x of Bi.

Keywords: DFT, Mg1-xBixO, pseudo-potential, rock-salt, wurtzite

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Authors: Anjali Uday, Yuting Wang, Andres Alfonso Pena Olare

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The Discrete Element Method is a promising approach to modeling microscopic behaviors of granular materials. The quality of the simulations however depends on the model parameters utilized. The present study focuses on calibration and validation of the discrete element parameters for Cuxhaven sand based on the experimental data from triaxial and oedometer tests. A sensitivity analysis was conducted during the sample preparation stage and the shear stage of the triaxial tests. The influence of parameters like rolling resistance, inter-particle friction coefficient, confining pressure and effective modulus were investigated on the void ratio of the sample generated. During the shear stage, the effect of parameters like inter-particle friction coefficient, effective modulus, rolling resistance friction coefficient and normal-to-shear stiffness ratio are examined. The calibration of the parameters is carried out such that the simulations reproduce the macro mechanical characteristics like dilation angle, peak stress, and stiffness. The above-mentioned calibrated parameters are then validated by simulating an oedometer test on the sand. The oedometer test results are in good agreement with experiments, which proves the suitability of the calibrated parameters. In the next step, the calibrated and validated model parameters are applied to forecast the micromechanical behavior including the evolution of contact force chains, buckling of columns of particles, observation of non-coaxiality, and sample inhomogeneity during a simple shear test. The evolution of contact force chains vividly shows the distribution, and alignment of strong contact forces. The changes in coordination number are in good agreement with the volumetric strain exhibited during the simple shear test. The vertical inhomogeneity of void ratios is documented throughout the shearing phase, which shows looser structures in the top and bottom layers. Buckling of columns is not observed due to the small rolling resistance coefficient adopted for simulations. The non-coaxiality of principal stress and strain rate is also well captured. Thus the micromechanical behaviors are well described using the calibrated and validated material parameters.

Keywords: discrete element model, parameter calibration, triaxial test, oedometer test, simple shear test

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 232

Authors: Xiaoyang Zhao, Kaiying Wang

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The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

Procedia PDF Downloads 140

Authors: Mohammad Hedar

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This paper presents selected topics from the area of high-speed electrical machine control with a focus on loss minimization. It focuses on pulse amplitude modulation (PAM) set-up in order to minimize the inrush current peak. An overview of these machines and the control topologies that have been used with these machines are reported. The critical problem that happens when controlling a high-speed electrical motor is the high current peak in the start-up process, which will cause high power-losses. The main goal of this paper is to clarify how the inrush current peak can be minimized in the start-up process. PAM control method is proposed to use in the frequency inverter, simulation results for PAM & PWM control method, and steps to improve the PAM control are reported. The simulations were performed with data for PMSM (nominal speed: 25 000 min-1, power: 3.1 kW, load: 1.2 Nm).

Keywords: control topology, frequency inverter, high-speed electrical machines, PAM, power losses, PWM

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Authors: Artion Kashuri, Rozana Liko

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In this paper, some generalization integral inequalities of Hermite–Hadamard type for functions whose derivatives are s–convex in modulus are given by using k–fractional integrals. Some applications to special means are obtained as well. Some known versions are recovered as special cases from our results. We note that our inequalities can be viewed as new refinements of the previous results. Finally, our results have a deep connection with various fractional integral operators and interested readers can find new interesting results using our idea and technique as well.

Keywords: Hermite-Hadamard's inequalities, Hölder's inequality, k-Riemann-Liouville fractional integral, special means

Procedia PDF Downloads 109

Authors: Sherine Farrag

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Currently-used MRI scanners in Cairo City possess static magnetic field (SMF) that varies from 0.25 up to 3T. More than half of them possess SMF of 1.5T. The SMF of the magnet determine the diagnostic power of a scanner, but not worker's exposure profile. This research paper presents an approach for numerical computation of induced electric fields and SAR values by estimation of fringe static magnetic fields. Iso-gauss line of MR was mapped and a polynomial function of the 7th degree was generated and tested. Induced current field due to worker motion in the SMF and SAR values for organs and tissues have been calculated. Results illustrate that the computation tool used permits quick accurate MRI iso-gauss mapping and calculation of SAR values which can then be used for assessment of occupational exposure profile of MRI operators.

Keywords: MRI occupational exposure, MRI safety, induced current density, specific absorption rate, static magnetic fields

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Authors: Martin Arguelles Perez, Woosoon Yim, Alexander Barzilov

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High-fidelity radiation monitoring is an essential component in the enhancement of the situational awareness capabilities of the Department of Energy’s Office of Environmental Management (DOE-EM) personnel. In this paper, multiple units of unmanned aerial vehicles (UAVs) each equipped with a cadmium zinc telluride (CZT) gamma-ray sensor are used for radiation source localization, which can provide vital real-time data for the EM tasks. To achieve this goal, a fully autonomous system of multicopter-based UAV swarm in 3D tetrahedron formation is used for surveying the area of interest and performing radiation source localization. The CZT sensor used in this study is suitable for small-size multicopter UAVs due to its small size and ease of interfacing with the UAV’s onboard electronics for high-resolution gamma spectroscopy enabling the characterization of radiation hazards. The multicopter platform with a fully autonomous flight feature is suitable for low-altitude applications such as radiation contamination sites. The conventional approach uses a single UAV mapping in a predefined waypoint path to predict the relative location and strength of the source, which can be time-consuming for radiation localization tasks. The proposed UAV swarm-based approach can significantly improve its ability to search for and track radiation sources. In this paper, two approaches are developed using (a) 2D planar circular (3 UAVs) and (b) 3D tetrahedron formation (4 UAVs). In both approaches, accurate estimation of the gradient vector is crucial for heading angle calculation. Each UAV carries the CZT sensor; the real-time radiation data are used for the calculation of a bulk heading vector for the swarm to achieve a UAV swarm’s source-seeking behavior. Also, a spinning formation is studied for both cases to improve gradient estimation near a radiation source. In the 3D tetrahedron formation, a UAV located closest to the source is designated as a lead unit to maintain the tetrahedron formation in space. Such a formation demonstrated a collective and coordinated movement for estimating a gradient vector for the radiation source and determining an optimal heading direction of the swarm. The proposed radiation localization technique is studied by computer simulation and validated experimentally in the indoor flight testbed using gamma sources. The technology presented in this paper provides the capability to readily add/replace radiation sensors to the UAV platforms in the field conditions enabling extensive condition measurement and greatly improving situational awareness and event management. Furthermore, the proposed radiation localization approach allows long-term measurements to be efficiently performed at wide areas of interest to prevent disasters and reduce dose risks to people and infrastructure.

Keywords: radiation, unmanned aerial system(UAV), source localization, UAV swarm, tetrahedron formation

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Authors: S. H. Lee, M. J. Park, O. M. Kwon

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In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of this systems are obtained by solving a set of Linear Matrix Inequalities(LMIs). One numerical example is included to show the effectiveness of the proposed criteria.

Keywords: multi-agent, linear matrix inequalities (LMIs), kronecker product, sampled-data, Lyapunov method

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Authors: Talah Aissa

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This paper reports an experimental study of the influence of marble powder used as a partial substitute for Portland cement (PC) on the mechanical properties and durability of high-performance concretes. The analysis of the experimental results on concrete at 15% content of marble powder with a fineness modulus of 11500 cm2/g, in a chloride environment, showed that it contributes positively to the perfection of its mechanical characteristics, its durability with respect to migration of chloride ions and oxygen permeability. On the basis of the experiments performed, it can be concluded that the marble powder is suitable for formulation of high performance concretes (HPC) and their properties are significantly better compared to the reference concrete (RC).

Keywords: marble powder, durability, concrete, cement

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Authors: Touati Mawloud

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Between electronics and electrical systems has developed a new technology that is power electronics, also called electronic of strong currents, this application covers a very wide range of use particularly in the industrial sector, where direct current engines are frequently used, they control their speed by the use of the converters (DC-DC), which aims to deal with various mechanical disturbances (fillers) or electrical (power). In future, it will play a critical role in transforming the current electric grid into the next generation grid. Existing silicon-based PE devices enable electric grid functionalities such as fault-current limiting and converter devices. Systems of future are envisioned to be highly automated, interactive "smart" grid that can self-adjust to meet the demand for electricity reliability, securely, and economically. Transforming today’s electric grid to the grid of the future will require creating or advancing a number of technologies, tools, and techniques—specifically, the capabilities of power electronics (PE). PE devices provide an interface between electrical system, and electronics system by converting AC to direct current (DC) and vice versa. Solid-state wide Bandgap (WBG), semiconductor electronics (such as silicon carbide [SiC], gallium nitride [GaN], and diamond) are envisioned to improve the reliability and efficiency of the next-generation grid substantially.

Keywords: Power Electronics (PE), electrical system generation electric grid, switching frequencies, converter devices

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Authors: R. Meier, M. Pander

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In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: lamb waves, industry 4.0, process control, elasticity, acoustoelasticity, microstructure

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Doo Byong Bae, Jae Jun Yoo, Il Gyu Park, Choi Seowon, Oh Chang Kook

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There are several wind load provisions to evaluate the wind response on tank structures such as API, Euro-code, etc. the assessment of wind action applying these provisions is made by performing the finite element analysis using both linear bifurcation analysis and geometrically nonlinear analysis. By comparing the pressure patterns obtained from the analysis with the results of wind tunnel test, most appropriate wind load criteria will be recommended.

Keywords: wind load, finite element analysis, linear bifurcation analysis, geometrically nonlinear analysis

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

Abstract:

In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

Procedia PDF Downloads 121

Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

Abstract:

In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

Procedia PDF Downloads 29

Authors: Myungkyu Park, Minkun Kim, Sunghoon Kim, Samgon Ryu

Abstract:

Recently, research for reactive fabrics which have the characteristics of CWA (Chemical Warfare Agent) decomposition is being performed actively. The performance level of decomposition for CWA decomposition in various environmental condition is one of the critical factors in applicability as protective materials for NBC (Nuclear, Biological, and Chemical) protective clothing. In this study, results of performance test for CWA decomposition by reactive fabric made of electrospinning web and reactive particle are presented. Currently, the MOF (metal organic framework) type of UiO-66-NH₂ is frequently being studied as material for decomposing CWA especially blister agent HD [Bis(2-chloroethyl) sulfide]. When we test decomposition rate with electrospinning web made of PVB (Polyvinyl Butiral) polymer and UiO-66-NH₂ particle, we can get very high protective performance than the case other particles are applied. Furthermore, if the repellant surface fabric is added on reactive material as the component of protective fabric, the performance of layer by layered reactive fabric could be approached to the level of current NBC protective fabric for HD decomposition rate. Reactive fabric we used in this study is manufactured by electrospinning process of polymer which contains the reactive particle of UiO-66-NH₂, and we performed crystalizing process once again on that polymer fiber web in solvent systems as a second step for manufacturing reactive fabric. Three kinds of polymer materials are used in this process, but PVB was most suitable as an electrospinning fiber polymer considering the shape of product. The density of particle on fiber web and HD decomposition rate is enhanced by secondary crystallization compared with the results which are not processed. The amount of HD penetration by 24hr AVLAG (Aerosol Vapor Liquid Assessment Group) swatch test through the reactive fabrics with secondary crystallization and without crystallization is 24 and 146μg/cm² respectively. Even though all of the reactive fiber webs for this test are combined with repellant surface layer at outer side of swatch, the effects of secondary crystallization of particle for the reactive fiber web are remarkable.

Keywords: CWA, Chemical Warfare Agent, gas decomposition, particle growth, protective clothing, reactive fabric, swatch test

Procedia PDF Downloads 278