Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 50

Search results for: extrapolation

50 Characterization of an Extrapolation Chamber for Dosimetry of Low Energy X-Ray Beams

Authors: Fernanda M. Bastos, Teógenes A. da Silva

Abstract:

Extrapolation chambers were designed to be used as primary standard dosimeter for measuring absorbed dose in a medium in beta radiation and low energy x-rays. The International Organization for Standardization established series of reference x-radiation for calibrating and determining the energy dependence of dosimeters that are to be reproduced in metrology laboratories. Standardization of the low energy x-ray beams with tube potential lower than 30 kV may be affected by the instrument used for dosimetry. In this work, parameters of a 23392 model PTW extrapolation chamber were determined aiming its use in low energy x-ray beams as a reference instrument.

Keywords: extrapolation chamber, low energy x-rays, x-ray dosimetry, X-ray metrology

Procedia PDF Downloads 307
49 An Approach for Estimation in Hierarchical Clustered Data Applicable to Rare Diseases

Authors: Daniel C. Bonzo

Abstract:

Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

Procedia PDF Downloads 53
48 Rough Oscillatory Singular Integrals on Rⁿ

Authors: H. M. Al-Qassem, L. Cheng, Y. Pan

Abstract:

In this paper we establish sharp bounds for oscillatory singular integrals with an arbitrary real polynomial phase P. Our kernels are allowed to be rough both on the unit sphere and in the radial direction. We show that the bounds grow no faster than log(deg(P)), which is optimal and was first obtained by Parissis and Papadimitrakis for kernels without any radial roughness. Among key ingredients of our methods are an L¹→L² estimate and extrapolation.

Keywords: oscillatory singular integral, rough kernel, singular integral, Orlicz spaces, Block spaces, extrapolation, L^{p} boundedness

Procedia PDF Downloads 162
47 A Hybrid Genetic Algorithm and Neural Network for Wind Profile Estimation

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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46 Sharp Estimates of Oscillatory Singular Integrals with Rough Kernels

Authors: H. Al-Qassem, L. Cheng, Y. Pan

Abstract:

In this paper, we establish sharp bounds for oscillatory singular integrals with an arbitrary real polynomial phase P. Our kernels are allowed to be rough both on the unit sphere and in the radial direction. We show that the bounds grow no faster than log (deg(P)), which is optimal and was first obtained by Parissis and Papadimitrakis for kernels without any radial roughness. Our results substantially improve many previously known results. Among key ingredients of our methods are an L¹→L² sharp estimate and using extrapolation.

Keywords: oscillatory singular integral, rough kernel, singular integral, orlicz spaces, block spaces, extrapolation, L^{p} boundedness

Procedia PDF Downloads 283
45 SIF Computation of Cracked Plate by FEM

Authors: Sari Elkahina, Zergoug Mourad, Benachenhou Kamel

Abstract:

The main purpose of this paper is to perform a computations comparison of stress intensity factor 'SIF' evaluation in case of cracked thin plate with Aluminum alloy 7075-T6 and 2024-T3 used in aeronautics structure under uniaxial loading. This evaluation is based on finite element method with a virtual power principle through two techniques: the extrapolation and G−θ. The first one consists to extrapolate the nodal displacements near the cracked tip using a refined triangular mesh with T3 and T6 special elements, while the second, consists of determining the energy release rate G through G−θ method by potential energy derivation which corresponds numerically to the elastic solution post-processing of a cracked solid by a contour integration computation via Gauss points. The SIF obtained results from extrapolation and G−θ methods will be compared to an analytical solution in a particular case. To illustrate the influence of the meshing kind and the size of integration contour position simulations are presented and analyzed.

Keywords: crack tip, SIF, finite element method, concentration technique, displacement extrapolation, aluminum alloy 7075-T6 and 2024-T3, energy release rate G, G-θ method, Gauss point numerical integration

Procedia PDF Downloads 246
44 Applications of Probabilistic Interpolation via Orthogonal Matrices

Authors: Dariusz Jacek Jakóbczak

Abstract:

Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.

Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation

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43 A Generalization of Option Pricing with Discrete Dividends to Markets with Daily Price Limits

Authors: Jiahau Guo, Yihe Zhang

Abstract:

This paper proposes solutions for pricing options on stocks paying discrete dividends in markets with daily price limits. We first extend the intraday density function of Guo and Chang (2020) to a multi-day one and use the framework of Haug et al. (2003) to value European options on stocks paying discrete dividends. Next, we adopt the fast Fourier transform (FFT) to derive accurate and efficient formulae for American options and further employ the three-point Richardson extrapolation to accelerate the computation. Finally, the accuracy of our proposed methods is verified by simulations.

Keywords: daily price limit, discrete dividend, early exercise, fast Fourier transform, multi-day density function, Richardson extrapolation

Procedia PDF Downloads 75
42 Computational Modeling of Load Limits of Carbon Fibre Composite Laminates Subjected to Low-Velocity Impact Utilizing Convolution-Based Fast Fourier Data Filtering Algorithms

Authors: Farhat Imtiaz, Umar Farooq

Abstract:

In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

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41 Imbalanced Time-Series Data Regression Using Conditional Generative Adversarial Networks

Authors: Murtadha D. Hssayeni, Behnaz Ghoraani

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During the collection of time-series data, many reasons lead to imbalanced and incomplete datasets. Consequently, when training deep convolutional models on these datasets, the models suffer from overfitting and lack generalizability to unseen data. In this paper, we investigated a new framework of Conditional Generative Adversarial Networks (cGANs) as a solution to improve the extrapolation and generalizability of the regression models in such datasets. We used an imbalanced synthetic dataset and two real-world datasets in Parkinson's disease (PD) application domain and Negative Affect (NA) estimation. In all scenarios, the developed cGAN demonstrated significantly better generalizability to unseen data samples than a traditional Convolutional Neural Network with an average improvement of 56% in mean absolute error in the case of the synthetic dataset, 34% in the PD dataset, and 18% in the NA dataset.

Keywords: regression, generative adversarial networks, imbalanced time-series data, incomplete data extrapolation

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40 Investigation of Threshold Voltage Shift in Gamma Irradiated N-Channel and P-Channel MOS Transistors of CD4007

Authors: S. Boorboor, S. A. H. Feghhi, H. Jafari

Abstract:

The ionizing radiations cause different kinds of damages in electronic components. MOSFETs, most common transistors in today’s digital and analog circuits, are severely sensitive to TID damage. In this work, the threshold voltage shift of CD4007 device, which is an integrated circuit including P-channel and N-channel MOS transistors, was investigated for low dose gamma irradiation under different gate bias voltages. We used linear extrapolation method to extract threshold voltage from ID-VG characteristic curve. The results showed that the threshold voltage shift was approximately 27.5 mV/Gy for N-channel and 3.5 mV/Gy for P-channel transistors at the gate bias of |9 V| after irradiation by Co-60 gamma ray source. Although the sensitivity of the devices under test were strongly dependent to biasing condition and transistor type, the threshold voltage shifted linearly versus accumulated dose in all cases. The overall results show that the application of CD4007 as an electronic buffer in a radiation therapy system is limited by TID damage. However, this integrated circuit can be used as a cheap and sensitive radiation dosimeter for accumulated dose measurement in radiation therapy systems.

Keywords: threshold voltage shift, MOS transistor, linear extrapolation, gamma irradiation

Procedia PDF Downloads 192
39 Compilation of Load Spectrum of Loader Drive Axle

Authors: Wei Yongxiang, Zhu Haoyue, Tang Heng, Yuan Qunwei

Abstract:

In order to study the preparation method of gear fatigue load spectrum for loaders, the load signal of four typical working conditions of loader is collected. The signal that reflects the law of load change is obtained by preprocessing the original signal. The torque of the drive axle is calculated by using the rain flow counting method. According to the operating time ratio of each working condition, the two-dimensional load spectrum based on the real working conditions of the drive axle of loader is established by the cycle extrapolation and synthesis method. The two-dimensional load spectrum is converted into one-dimensional load spectrum by means of the mean of torque equal damage method. Torque amplification includes the maximum load torque of the main reduction gear. Based on the theory of equal damage, the accelerated cycles are calculated. In this way, the load spectrum of the loading condition of the drive axle is prepared to reflect loading condition of the loader. The load spectrum can provide reference for fatigue life test and life prediction of loader drive axle.

Keywords: load spectrum, axle, torque, rain-flow counting method, extrapolation

Procedia PDF Downloads 195
38 Accelerated Molecular Simulation: A Convolution Approach

Authors: Jannes Quer, Amir Niknejad, Marcus Weber

Abstract:

Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

Procedia PDF Downloads 249
37 A Cohesive Zone Model with Parameters Determined by Uniaxial Stress-Strain Curve

Authors: Y.J. Wang, C. Q. Ru

Abstract:

A key issue of cohesive zone models is how to determine the cohesive zone model parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model (CZM): The maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is modeled by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.

Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral

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36 Determination of Cohesive Zone Model’s Parameters Based On the Uniaxial Stress-Strain Curve

Authors: Y. J. Wang, C. Q. Ru

Abstract:

A key issue of cohesive zone models is how to determine the cohesive zone model (CZM) parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model: the maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is simulated by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.

Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral

Procedia PDF Downloads 433
35 Enhancing Temporal Extrapolation of Wind Speed Using a Hybrid Technique: A Case Study in West Coast of Denmark

Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

Procedia PDF Downloads 61
34 Prediction of Wind Speed by Artificial Neural Networks for Energy Application

Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

Abstract:

In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

Procedia PDF Downloads 589
33 [Keynote Speech]: Competitive Evaluation of Power Plants in Energy Policy

Authors: Beril Tuğrul

Abstract:

Electrical energy is the most important form of energy and electrical power plants have highest impact factor in energy policy. This study is in relation with evaluation of various power plants including fossil fuels, nuclear and renewable energy based power plants. The power plants evaluated with regard to their overall impact that considered for establishing of the plants. Both positive and negative impacts of power plant operation are compared view of different arguments. Then calculate the impact factor by using variation linear extrapolation for each argument. With this study, power plants assessed with the different point of view and clarified objectively.

Keywords:

Procedia PDF Downloads 375
32 Relevancy Measures of Errors in Displacements of Finite Elements Analysis Results

Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

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This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

Procedia PDF Downloads 324
31 Investigation of VN/TiN Multilayer Coatings on AZ91D Mg Alloys

Authors: M. Ertas, A. C. Onel, G. Ekinci, B. Toydemir, S. Durdu, M. Usta, L. Colakerol Arslan

Abstract:

To develop AZ91D magnesium alloys with improved properties, we have applied TiN and VN/TiN multilayer coatings using DC magnetron sputter technique. Coating structure, surface morphology, chemical bonding and corrosion resistance of coatings were analyzed by x-ray diffraction (XRD), scanning electron microscope (SEM), x-ray photoelectron spectroscopy (XPS), and tafel extrapolation method, respectively. XPS analysis reveal that VN overlayer reacts with oxygen at the VN/TiN interface and forms more stable TiN layer. Morphological investigations and the corrosion results show that VN/TiN multilayer thin film coatings are quite effective to optimize the corrosion resistance of Mg alloys.

Keywords: AZ91D Mg alloys, high corrosion resistance, transition metal nitride coatings, magnetron sputter

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30 Leading People in a Digital Era: A Theoretical Study of Challenges and Opportunities of Online Networking Platforms

Authors: Pawel Korzynski

Abstract:

Times where leaders communicate mainly while walking along the hallways have passed away. Currently, millennials, people that were born between the early 1980s and the early 2000s, extensively use applications based on Web 2.0 model that assumes content creation and edition by all Internet users in a collaborative fashion. Leaders who are willing to engage their subordinates in a digital era, increasingly often use above-mentioned applications. This paper discusses challenges and opportunities that are related to leaders’ online networking. First, online networking-related terms that appeared in literature are analyzed. Then, types of online networking platforms for leaders and ways how these platforms can be used are discussed. Finally, several trends in online networking studies and extrapolation of some findings to leadership are explained.

Keywords: social media, digital era, leadership, online networking

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29 Catalytic Nanomaterials for Energy Conversion and Storage

Authors: Yijin Kang

Abstract:

Chemical-electrical energy conversion and storage are greatly attractive for the development of sustainable energy. Catalytic processes are heavily involved in such energy conversion and storage. Development of high-performance catalyst nanomaterials relies on tuning material structures at nanoscale. This is in particular manifested in the design of catalysts demanding both high activity and durability. Here, a research system will be presented that connects fundamental investigation on well-defined extended surfaces (e.g. single crystal surfaces), extrapolation onto nanocrystals with highly controlled shape and size, exploration of interfacial interaction using novel nanocrystal superlattices as platform, and finally design of high performance catalysts in which all the possible beneficial properties from complex functional structures are implemented. Using recently published results, it will be demonstrated that optimal and fine balanced activity and durability, as well as tunable functionality, can be achieved by carefully tailoring the nanostructure of catalytic nanomaterials.

Keywords: energy, nanomaterials, catalysis, electrocatalysis

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28 Evaluation of Corrosion Property of Aluminium-Zirconium Dioxide (AlZrO2) Nanocomposites

Authors: M. Ramachandra, G. Dilip Maruthi, R. Rashmi

Abstract:

This paper aims to study the corrosion property of aluminum matrix nanocomposite of an aluminum alloy (Al-6061) reinforced with zirconium dioxide (ZrO2) particles. The zirconium dioxide particles are synthesized by solution combustion method. The nanocomposite materials are prepared by mechanical stir casting method, varying the percentage of n-ZrO2 (2.5%, 5% and 7.5% by weight). The corrosion behavior of base metal (Al-6061) and Al/ZrO2 nanocomposite in seawater (3.5% NaCl solution) is measured using the potential control method. The corrosion rate is evaluated by Tafel extrapolation technique. The corrosion potential increases with the increase in wt.% of n-ZrO2 in the nanocomposite which means the decrease in corrosion rate. It is found that on addition of n-ZrO2 particles to the aluminum matrix, the corrosion rate has decreased compared to the base metal.

Keywords: Al6061 alloy, corrosion, solution, stir casting, combustion, potentiostat, zirconium dioxide

Procedia PDF Downloads 274
27 Geochemical Investigation of Weathering and Sorting for Tepeköy Sandstones

Authors: M. Yavuz Hüseyinca, Şuayip Küpeli

Abstract:

The Chemical Index of Alteration (CIA) values of Late Eocene-Oligocene aged sandstones that exposed on the eastern edge of Tuz Lake (Central Anatolia, Turkey) range from 49 to 59 with an average of 51. The A-CN-K diagram indicates that sandstones underwent post-depositional K-metasomatism. The original average CIA value before the K-metasomatism is calculated as 55. This value is lower than that of Post Archean Australian Shale (PAAS) and defines a low intense chemical weathering in the source-area. Extrapolation of sandstones back to the plagioclase-alkali feldspar line in the A-CN-K diagram suggests a high average plagioclase to alkali feldspar ratio in the provenance and a composition close to granodiorite. The Zr/Sc and Th/Sc ratios with the Al₂O₃-Zr-TiO₂ space do not show zircon addition that refuse both recycling of sediments and sorting effect. All these data suggest direct and rapid transportation from the source due to topographic uplift and probably arid to semi-arid climate conditions for the sandstones.

Keywords: central Anatolia, sandstone, sorting, weathering

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26 Diversity in Finance Literature Revealed through the Lens of Machine Learning: A Topic Modeling Approach on Academic Papers

Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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25 Provenance and Paleoweathering Conditions of Doganhisar Clay Beds

Authors: Mehmet Yavuz Huseyinca

Abstract:

The clay beds are located at the south-southeast of Doğanhisar and northwest of Konya in the Central Anatolia. In the scope of preliminary study, three types of samples were investigated including basement phyllite (Bp) overlain by the clay beds, weathered phyllite (Wp) and Doğanhisar clay (Dc). The Chemical Index of Alteration (CIA) values of Dc range from 81 to 88 with an average of 85. This value is higher than that of Post Archean Australian Shale (PAAS) and defines very intense chemical weathering in the source-area. On the other hand, the A-CN-K diagram indicates that Bp underwent high degree post-depositional K-metasomatism. The average reconstructed CIA value of the Bp prior to the K-metasomatism is mainly 81 which overlaps the CIA values of the Wp (83) and Dc (85). Similar CIA values indicate parallel weathering trends. Also, extrapolation of the samples back to the plagioclase-alkali feldspar line in the A-CN-K diagram suggests an identical provenance close to granite in composition. Hereby the weathering background of Dc includes two steps. First one is intense weathering process of a granitic source to Bp with post-depositional K-metasomatism and the latter is progressively weathering of Bp to premetasomatised conditions (formation of Wp) ending with Dc deposition.

Keywords: clay beds, Doganhisar, provenance, weathering

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24 Developing a Web GIS Tool for the Evaluation of Soil Erosion of a Watershed

Authors: Y. Fekir, K. Mederbal, M. A. Hamadouche, D. Anteur

Abstract:

The soil erosion by water has become one of the biggest problems of the environment in the world, threatening the majority of countries. There are several models to evaluate erosion. These models are still a simplified representation of reality. They permit the analysis of complex systems, measurements are complementary to allow an extrapolation in time and space and may combine different factors. The empirical model of soil loss proposed by Wischmeier and Smith (Universal Soil Loss Equation), is widely used in many countries. He considers that erosion is a multiplicative function of five factors: rainfall erosivity (the R factor) the soil erodibility factor (K), topography (LS), the erosion control practices (P) and vegetation cover and agricultural practices (C). In this work, we tried to develop a tool based on Web GIS functionality to evaluate soil losses caused by erosion taking into account five factors. This tool allows the user to integrate all the data needed for the evaluation (DEM, Land use, rainfall ...) in the form of digital layers to calculate the five factors taken into account in the USLE equation (R, K, C, P, LS). Accordingly, and after treatment of the integrated data set, a map of the soil losses will be achieved as a result. We tested the proposed tool on a watershed basin located in the weste of Algeria where a dataset was collected and prepared.

Keywords: USLE, erosion, web gis, Algeria

Procedia PDF Downloads 248
23 Effect of Al2O3 Nanoparticles on Corrosion Behavior of Aluminum Alloy Fabricated by Powder Metallurgy

Authors: Muna Khethier Abbass, Bassma Finner Sultan

Abstract:

In this research the effect of Al2O3 nanoparticles on corrosion behavior of aluminum base alloy(Al-4.5wt%Cu-1.5wt%Mg) has been investigated. Nanocomopsites reinforced with variable contents of 1,3 & 5wt% of Al2O3 nanoparticles were fabricated using powder metallurgy. All samples were prepared from the base alloy powders under the best powder metallurgy processing conditions of 6 hr of mixing time , 450 MPa of compaction pressure and 560°C of sintering temperature. Density and micro hardness measurements, and electrochemical corrosion tests are performed for all prepared samples in 3.5wt%NaCl solution at room temperature using potentiostate instrument. It has been found that density and micro hardness of the nanocomposite increase with increasing of wt% Al2O3 nanoparticles to Al matrix. It was found from Tafel extrapolation method that corrosion rates of the nanocomposites reinforced with alumina nanoparticles were lower than that of base alloy. From results of corrosion test by potentiodynamic cyclic polarization method, it was found the pitting corrosion resistance improves with adding of Al2O3 nanoparticles . It was noticed that the pits disappear and the hysteresis loop disappears also from anodic polarization curve.

Keywords: powder metallurgy, nano composites, Al-Cu-Mg alloy, electrochemical corrosion

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22 Prediction of Temperature Distribution during Drilling Process Using Artificial Neural Network

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

Abstract:

Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

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21 Simulation of Hydrogenated Boron Nitride Nanotube’s Mechanical Properties for Radiation Shielding Applications

Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

Abstract:

Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B10’s large neutron capture cross section. The B10 has an effective neutron capture cross section suitable for low energy neutrons ranging from 10-5 to 104 eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm3. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: boron nitride nanotube, radiation shielding, young modulus, atomistic modeling

Procedia PDF Downloads 210