Search results for: wave propagation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2016

Search results for: wave propagation

966 Ontology-Based Backpropagation Neural Network Classification and Reasoning Strategy for NoSQL and SQL Databases

Authors: Hao-Hsiang Ku, Ching-Ho Chi

Abstract:

Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

Procedia PDF Downloads 262
965 60 GHz Multi-Sector Antenna Array with Switchable Radiation-Beams for Small Cell 5G Networks

Authors: N. Ojaroudi Parchin, H. Jahanbakhsh Basherlou, Y. Al-Yasir, A. M. Abdulkhaleq, R. A. Abd-Alhameed, P. S. Excell

Abstract:

A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1×8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.

Keywords: mm-wave communications, multi-sector array, patch antenna, small cell networks

Procedia PDF Downloads 157
964 Forecasting Electricity Spot Price with Generalized Long Memory Modeling: Wavelet and Neural Network

Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

Abstract:

This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

Procedia PDF Downloads 231
963 Asymptotic Expansion of the Korteweg-de Vries-Burgers Equation

Authors: Jian-Jun Shu

Abstract:

It is common knowledge that many physical problems (such as non-linear shallow-water waves and wave motion in plasmas) can be described by the Korteweg-de Vries (KdV) equation, which possesses certain special solutions, known as solitary waves or solitons. As a marriage of the KdV equation and the classical Burgers (KdVB) equation, the Korteweg-de Vries-Burgers (KdVB) equation is a mathematical model of waves on shallow water surfaces in the presence of viscous dissipation. Asymptotic analysis is a method of describing limiting behavior and is a key tool for exploring the differential equations which arise in the mathematical modeling of real-world phenomena. By using variable transformations, the asymptotic expansion of the KdVB equation is presented in this paper. The asymptotic expansion may provide a good gauge on the validation of the corresponding numerical scheme.

Keywords: asymptotic expansion, differential equation, Korteweg-de Vries-Burgers (KdVB) equation, soliton

Procedia PDF Downloads 249
962 Structural, Electronic and Optical Properties of LiₓNa1-ₓH for Hydrogen Storage

Authors: B. Bahloul

Abstract:

This study investigates the structural, electronic, and optical properties of LiH and NaH compounds, as well as their ternary mixed crystals LiₓNa1-ₓH, adopting a face-centered cubic structure with space group Fm-3m (number 225). The structural and electronic characteristics are examined using density functional theory (DFT), while empirical methods, specifically the modified Moss relation, are employed for analyzing optical properties. The exchange-correlation potential is determined through the generalized gradient approximation (PBEsol-GGA) within the density functional theory (DFT) framework, utilizing the projected augmented wave pseudopotentials (PAW) approach. The Quantum Espresso code is employed for conducting these calculations. The calculated lattice parameters at equilibrium volume and the bulk modulus for x=0 and x=1 exhibit good agreement with existing literature data. Additionally, the LiₓNa1-ₓH alloys are identified as having a direct band gap.

Keywords: DFT, structural, electronic, optical properties

Procedia PDF Downloads 71
961 Relation between Energy Absorption and Box Dimension of Rock Fragments under Impact Loading

Authors: Li Hung-Hui, Chen Chi-Chieh, Yang Zon-Yee

Abstract:

This study aims to explore the impact energy absorption in the fragmented processes of rock samples during the split-Hopkinson-pressure-bar tests. Three kinds of rock samples including granite, marble and sandstone were tested. The impact energy absorptions were calculated according to the incident, reflected and transmitted strain wave histories measured by a oscilloscope. The degree of fragment rocks after tests was quantified by the box dimension of the fractal theory. The box dimension of rock fragments was obtained from the particle size distribution curve by the sieve analysis. The results can be concluded that: (1) the degree of rock fragments after tests can be well described by the value of box dimension; (2) with the impact energy absorption increasing, the degrees of rock fragments are varied from the very large fragments to very small fragments, and the corresponding box dimension varies from 2.9 to 1.2.

Keywords: SHPB test, energy absorption, rock fragments, impact loading, box dimension

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960 Investigation of Arson Fire Incident in Textile Garment Building Using Fire Dynamic Simulation

Authors: Mohsin Ali Shaikh, Song Weiguo, Muhammad Kashan Surahio, Usman Shahid, Rehmat Karim

Abstract:

This study investigated a catastrophic arson fire incident that occurred at a textile garment building in Karachi, Pakistan. Unfortunately, a catastrophic event led to the loss of 262 lives and caused 55 severe injuries. The primary objective is to analyze the aspects of the fire incident and understand the causes of arson fire disasters. The study utilized Fire Dynamic Simulation (F.D.S) was employed to simulate fire propagation, visibility, harmful gas concentration, fire temperature, and numerical results. The analysis report has determined the specific circumstances that created the unpleasant incident in the present study. The significance of the current findings lies in their potential to prevent arson fires, improve fire safety measures, and the development of safety plans in building design. The fire dynamic simulation findings can serve as a theoretical basis for the investigation of arson fires and evacuation planning in textile garment buildings.

Keywords: investigation, fire arson incident, textile garment, fire dynamic simulation (FDS)

Procedia PDF Downloads 90
959 Effect of Viscosity in Void Structure with Interacting Variable Charge Dust Grains

Authors: Nebbat El Amine

Abstract:

The void is a dust free region inside the dust cloud in the plasma. It is found that the dust grain charge variation lead to the extension of the void. Moreover, for bigger dust grains, it is seen that the wave-like structure recedes when charge variation is dealt with. Furthermore, as the grain-grain distance is inversely proportional to density, the grain-grain interaction gets more important for a denser dust population and is to be included in momentum equation. For the result indicate above, the plasma is considered non viscous. But in fact, it’s not always true. Some authors measured experimentally the viscosity of this background and found that the viscosity of dusty plasma increase with background gas pressure. In this paper, we tack account the viscosity of the fluid, and we compare the result with that found in the recent work.

Keywords: voids, dusty plasmas, variable charge, viscosity

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958 Simple Fabrication of Au (111)-Like Electrode and Its Applications to Electrochemical Determination of Dopamine and Ascorbic Acid

Authors: Zahrah Thamer Althagafi, Mohamed I. Awad

Abstract:

A simple method for the fabrication of Au (111)-like electrode via controlled reductive desorption of a pre-adsorbed cysteine monolayer onto polycrystalline gold (poly-Au) electrode is introduced. Then, the voltammetric behaviour of dopamine (DA) and ascorbic acid (AA) on the thus modified electrode is investigated. Electrochemical characterization of the modified electrode is achieved using cyclic voltammetry and square wave voltammetry. For the binary mixture of DA and AA, the results showed that Au (111)-like electrode exhibits excellent electrocatalytic activity towards the oxidation of DA and AA. This allows highly selective and simultaneous determination of DA and AA. The effect of various experimental parameters on the voltammetric responses of DA and AA was investigated. The enrichment of the Au (111) facet of the poly-Au electrode is thought to be behind the electrocatalytic activity.

Keywords: gold electrode, electroanalysis, electrocatalysis, monolayers, self-assembly, cysteine, dopamine, ascorbic acid

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957 Half Metallic Antiferromagnetic of Doped TiO2 Rutile with Doubles Impurities (Os, Mo) from Ab Initio Calculations

Authors: M. Fakhim Lamrani, M. Ouchri, M. Belaiche, El Kenz, M. Loulidi, A. Benyoussef

Abstract:

Electronic and magnetic calculations based on density functional theory within the generalized gradient approximation for II-VI compound semiconductor TiO2 doped with single impurity Os and Mo; these compounds are a half metallic ferromagnet in their ground state with a total magnetic moment of 2 μB for both systems. Then, TiO2 doped with double impurities Os and Mo have been performed. As result, Ti1-2xOsxMoxO2 with x=0.065 is half-metallic antiferromagnets with 100% spin polarization of the conduction electrons crossing the Fermi level, without showing a net magnetization. Moreover, Ti14OsMoO32 compound is stable energetically than Ti1-xMoxO2 and Ti1-xOsxO2. The antiferromagnetic interaction in Ti1-2xOsxMoxO2 system is attributed to the double exchange mechanism, and the latter could also be the origin of their half metallic.

Keywords: diluted magnetic semiconductor, half-metallic antiferromagnetic, augmented spherical wave method

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956 Estimation of Foliar Nitrogen in Selected Vegetation Communities of Uttrakhand Himalayas Using Hyperspectral Satellite Remote Sensing

Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

Abstract:

The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

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955 Coaxial Helix Antenna for Microwave Coagulation Therapy in Liver Tissue Simulations

Authors: M. Chaichanyut, S. Tungjitkusolmun

Abstract:

This paper is concerned with microwave (MW) ablation for a liver cancer tissue by using helix antenna. The antenna structure supports the propagation of microwave energy at 2.45 GHz. A 1½ turn spiral catheter-based microwave antenna applicator has been developed. We utilize the three-dimensional finite element method (3D FEM) simulation to analyze where the tissue heat flux, lesion pattern and volume destruction during MW ablation. The configurations of helix antenna where Helix air-core antenna and Helix Dielectric-core antenna. The 3D FEMs solutions were based on Maxwell and bio-heat equations. The simulation protocol was power control (10 W, 300s). Our simulation result, both helix antennas have heat flux occurred around the helix antenna and that can be induced the temperature distribution similar (teardrop). The region where the temperature exceeds 50°C the microwave ablation was successful (i.e. complete destruction). The Helix air-core antenna and Helix Dielectric-core antenna, ablation zone or axial ratios (Widest/length) were respectively 0.82 and 0.85; the complete destructions were respectively 4.18 cm³ and 5.64 cm³.

Keywords: liver cancer, Helix antenna, finite element, microwave ablation

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954 The Impact of Recurring Events in Fake News Detection

Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

Abstract:

Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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953 An Integrated Approach to Find the Effect of Strain Rate on Ultimate Tensile Strength of Randomly Oriented Short Glass Fiber Composite in Combination with Artificial Neural Network

Authors: Sharad Shrivastava, Arun Jalan

Abstract:

In this study tensile testing was performed on randomly oriented short glass fiber/epoxy resin composite specimens which were prepared using hand lay-up method. Samples were tested over a wide range of strain rate/loading rate from 2mm/min to 40mm/min to see the effect on ultimate tensile strength of the composite. A multi layered 'back propagation artificial neural network of supervised learning type' was used to analyze and predict the tensile properties with strain rate and temperature as given input and output as UTS to predict. Various network structures were designed and investigated with varying parameters and network sizes, and an optimized network structure was proposed to predict the UTS of short glass fiber/epoxy resin composite specimens with reasonably good accuracy.

Keywords: glass fiber composite, mechanical properties, strain rate, artificial neural network

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952 Profit-Based Artificial Neural Network (ANN) Trained by Migrating Birds Optimization: A Case Study in Credit Card Fraud Detection

Authors: Ashkan Zakaryazad, Ekrem Duman

Abstract:

A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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951 Exact Soliton Solutions of the Integrable (2+1)-Dimensional Fokas-Lenells Equation

Authors: Meruyert Zhassybayeva, Kuralay Yesmukhanova, Ratbay Myrzakulov

Abstract:

Integrable nonlinear differential equations are an important class of nonlinear wave equations that admit exact soliton solutions. All these equations have an amazing property which is that their soliton waves collide elastically. One of such equations is the (1+1)-dimensional Fokas-Lenells equation. In this paper, we have constructed an integrable (2+1)-dimensional Fokas-Lenells equation. The integrability of this equation is ensured by the existence of a Lax representation for it. We obtained its bilinear form from the Hirota method. Using the Hirota method, exact one-soliton and two-soliton solutions of the (2 +1)-dimensional Fokas-Lenells equation were found.

Keywords: Fokas-Lenells equation, integrability, soliton, the Hirota bilinear method

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950 Low Density Parity Check Codes

Authors: Kassoul Ilyes

Abstract:

The field of error correcting codes has been revolutionized by the introduction of iteratively decoded codes. Among these, LDPC codes are now a preferred solution thanks to their remarkable performance and low complexity. The binary version of LDPC codes showed even better performance, although it’s decoding introduced greater complexity. This thesis studies the performance of binary LDPC codes using simplified weighted decisions. Information is transported between a transmitter and a receiver by digital transmission systems, either by propagating over a radio channel or also by using a transmission medium such as the transmission line. The purpose of the transmission system is then to carry the information from the transmitter to the receiver as reliably as possible. These codes have not generated enough interest within the coding theory community. This forgetfulness will last until the introduction of Turbo-codes and the iterative principle. Then it was proposed to adopt Pearl's Belief Propagation (BP) algorithm for decoding these codes. Subsequently, Luby introduced irregular LDPC codes characterized by a parity check matrix. And finally, we study simplifications on binary LDPC codes. Thus, we propose a method to make the exact calculation of the APP simpler. This method leads to simplifying the implementation of the system.

Keywords: LDPC, parity check matrix, 5G, BER, SNR

Procedia PDF Downloads 153
949 Damage Assessment of Reinforced Concrete Slabs Subjected to Blast Loading

Authors: W. Badla

Abstract:

A numerical investigation has been carried out to examine the behaviour of reinforced concrete slabs to uniform blast loading. The aim of this work is to determine the effects of various parameters on the results. Finite element simulations were performed in the non linear dynamic range using an elasto-plastic damage model. The main parameters considered are: the negative phase of blast loading, time duration, equivalent weight of TNT, distance of the explosive and slab dimensions. Numerical modelling has been performed using ABAQUS/Explicit. The results obtained in terms of displacements and propagation of damage show that the above parameters influence considerably the nonlinear dynamic behaviour of reinforced concrete slabs under uniform blast loading.

Keywords: blast loading, reinforced concrete slabs, elasto-plastic damage model, negative phase, time duration, equivalent weight of TNT, explosive distance, slab dimensions

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948 Mitigation of Electromagnetic Interference Generated by GPIB Control-Network in AC-DC Transfer Measurement System

Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

Abstract:

The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

Procedia PDF Downloads 288
947 Simple Finite-Element Procedure for Modeling Crack Propagation in Reinforced Concrete Bridge Deck under Repetitive Moving Truck Wheel Loads

Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

Abstract:

Modeling cracks in concrete is complicated by its strain-softening behavior which requires the use of sophisticated energy criteria of fracture mechanics to assure stable and convergent solutions in the finite-element (FE) analysis particularly for relatively large structures. However, for small-scale structures such as beams and slabs, a simpler approach relies on retaining some shear stiffness in the cracking plane has been adopted in literature to model the strain-softening behavior of concrete under monotonically increased loading. According to the shear retaining approach, each element is assumed to be an isotropic material prior to cracking of concrete. Once an element is cracked, the isotropic element is replaced with an orthotropic element in which the new orthotropic stiffness matrix is formulated with respect to the crack orientation. The shear transfer factor of 0.5 is used in parallel to the crack plane. The shear retaining approach is adopted in this research to model cracks in RC bridge deck with some modifications to take into account the effect of repetitive moving truck wheel loads as they cause fatigue cracking of concrete. First modification is the introduction of fatigue tests of concrete and reinforcing steel and the Palmgren-Miner linear criterion of cumulative damage in the conventional FE analysis. For a certain loading, the number of cycles to failure of each concrete or RC element can be calculated from the fatigue or S-N curves of concrete and reinforcing steel. The elements with the minimum number of cycles to failure are the failed elements. For the elements that do not fail, the damage is accumulated according to Palmgren-Miner linear criterion of cumulative damage. The stiffness of the failed element is modified and the procedure is repeated until the deck slab fails. The total number of load cycles to failure of the deck slab can then be obtained from which the S-N curve of the deck slab can be simulated. Second modification is the modification in shear transfer factor. Moving loading causes continuous rubbing of crack interfaces which greatly reduces shear transfer mechanism. It is therefore conservatively assumed in this study that the analysis is conducted with shear transfer factor of zero for the case of moving loading. A customized FE program has been developed using the MATLAB software to accomodate such modifications. The developed procedure has been validated with the fatigue test of the 1/6.6-scale AASHTO bridge deck under the applications of both fixed-point repetitive loading and moving loading presented in the literature. Results are in good agreement both experimental vs. simulated S-N curves and observed vs. simulated crack patterns. Significant contribution of the developed procedure is a series of S-N relations which can now be simulated at any desired levels of cracking in addition to the experimentally derived S-N relation at the failure of the deck slab. This permits the systematic investigation of crack propagation or deterioration of RC bridge deck which is appeared to be useful information for highway agencies to prolong the life of their bridge decks.

Keywords: bridge deck, cracking, deterioration, fatigue, finite-element, moving truck, reinforced concrete

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946 New Isolate of Cucumber Mosaic Virus Infecting Banana

Authors: Abdelsabour G. A. Khaled, Ahmed W. A. Abdalla And Sabry Y. M. Mahmoud

Abstract:

Banana plants showing typical mosaic and yellow stripes on leaves as symptoms were collected from Assiut Governorate in Egypt. The causal agent was identified as Cucumber mosaic virus (CMV) on the basis of symptoms, transmission, serology, transmission electron microscopy and reverse transcription polymerase chain reaction (RT-PCR). Coat protein (CP) gene was amplified using gene specific primers for coat protein (CP), followed by cloning into desired cloning vector for sequencing. In this study the CMV was transmitted into propagation host either by aphid or mechanically. The transmission was confirmed through Direct Antigen Coating Enzyme Linked Immuno Sorbent Assay (DAC-ELISA). Analysis of the 120 deduced amino acid sequence of the coat protein gene revealed that the EG-A strain of CMV shared from 97.50 to 98.33% with those strains belonging to subgroup IA. The cluster analysis grouped the Egyptian isolate with strains Fny and Ri8 belonging sub-group IA. It appears that there occurs a high incidence of CMV infecting banana belonging to IA subgroup in most parts of Egypt.

Keywords: banana, CMV, transmission, CP gene, RT-PCR

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945 Auto Classification of Multiple ECG Arrhythmic Detection via Machine Learning Techniques: A Review

Authors: Ng Liang Shen, Hau Yuan Wen

Abstract:

Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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944 Innovation and Analysis of Vibrating Fork Level Switch

Authors: Kuen-Ming Shu, Cheng-Yu Chen

Abstract:

A vibrating-fork sensor can measure the level height of solids and liquids and operates according to the principle that vibrations created by piezoelectric ceramics are transmitted to the vibrating fork, which produces resonance. When the vibrating fork touches an object, its resonance frequency changes and produces a signal that returns to a controller for immediate adjustment, so as to effectively monitor raw material loading. The design of the vibrating fork in a vibrating-fork material sensor is crucial. In this paper, ANSYS finite element analysis software is used to perform modal analysis on the vibrations of the vibrating fork. In addition, to design and produce a superior vibrating fork, the dimensions and welding shape of the vibrating fork are compared in a simulation performed using the Taguchi method.

Keywords: vibrating fork, piezoelectric ceramics, sound wave, ANSYS, Taguchi method, modal analysis

Procedia PDF Downloads 249
943 Application of Artificial Neural Network for Prediction of Load-Haul-Dump Machine Performance Characteristics

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

Abstract:

Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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942 Novel CFRP Adhesive Joints and Structures for Offshore Application

Authors: M. R. Abusrea, Shiyi Jiang, Dingding Chen, Kazuo Arakawa

Abstract:

Novel wind-lens turbine designs can augment power output. Vacuum-Assisted Resin Transfer Molding (VARTM) is used to form large and complex structures from a Carbon Fiber Reinforced Polymer (CFRP) composite. Typically, wind-lens turbine structures are fabricated in segments, and then bonded to form the final structure. This paper introduces five new adhesive joints, divided into two groups: One is constructed between dry carbon and CFRP fabrics, and the other is constructed with two dry carbon fibers. All joints and CFRP fabrics were made in our laboratory using VARTM manufacturing techniques. Specimens were prepared for tensile testing to measure joint performance. The results showed that the second group of joints achieved a higher tensile strength than the first group. On the other hand, the tensile fracture behavior of the two groups showed the same pattern of crack originating near the joint ends followed by crack propagation until fracture.

Keywords: adhesive joints, CFRP, VARTM, resin transfer molding

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941 A Phase Field Approach to Model Crack Interface Interaction in Ceramic Matrix Composites

Authors: Dhaladhuli Pranavi, Amirtham Rajagopal

Abstract:

There are various failure modes in ceramic matrix composites; notable ones are fiber breakage, matrix cracking and fiber matrix debonding. Crack nucleation and propagation in microstructure of such composites requires an understanding of interaction of crack with the multiple inclusion heterogeneous system and interfaces. In order to assess structural integrity, the material parameters especially of the interface that governs the crack growth should be determined. In the present work, a nonlocal phase field approach is proposed to model the crack interface interaction in such composites. Nonlocal approaches help in understanding the complex mechanisms of delamination growth and mitigation and operates at a material length scale. The performance of the proposed formulation is illustrated through representative numerical examples. The model proposed is implemented in the framework of the finite element method. Several parametric studies on interface crack interaction are conducted. The proposed model is easy and simple to implement and works very well in modeling fracture in composite systems.

Keywords: composite, interface, nonlocal, phase field

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940 The Application of Artificial Neural Networks for the Performance Prediction of Evacuated Tube Solar Air Collector with Phase Change Material

Authors: Sukhbir Singh

Abstract:

This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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939 Interferometric Demodulation Scheme Using a Mode-Locker Fiber Laser

Authors: Liang Zhang, Yuanfu Lu, Yuming Dong, Guohua Jiao, Wei Chen, Jiancheng Lv

Abstract:

We demonstrated an interferometric demodulation scheme using a mode-locked fiber laser. The mode-locked fiber laser is launched into a two-beam interferometer. When the ratio between the fiber path imbalance of interferometer and the laser cavity length is close to an integer, an interferometric fringe emerges as a result of vernier effect, and then the phase shift of the interferometer can be demodulated. The mode-locked fiber laser provides a large bandwidth and reduces the cost for wavelength division multiplexion (WDM). The proposed interferometric demodulation scheme can be further applied in multi-point sensing system such as fiber optics hydrophone array, seismic wave detection network with high sensitivity and low cost.

Keywords: fiber sensing, interferometric demodulation, mode-locked fiber laser, vernier effect

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938 Boussinesq Model for Dam-Break Flow Analysis

Authors: Najibullah M, Soumendra Nath Kuiry

Abstract:

Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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937 A Neural Network Modelling Approach for Predicting Permeability from Well Logs Data

Authors: Chico Horacio Jose Sambo

Abstract:

Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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