Search results for: modeling accuracy

Authors: Burçin Saltık, Levent Genç

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In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.

Keywords: landsat 8 (OLI-TIRS), LST, LSWI, LULC, NDVI, rice

Procedia PDF Downloads 214

Authors: Xue Xiao, Sun Hao, Liu Donghua

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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.

Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment

Procedia PDF Downloads 348

Authors: Prashant Pandey

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In the present article, an effective Laguerre collocation method is used to obtain the approximate solution of a system of coupled fractional-order non-linear reaction-advection-diffusion equation with prescribed initial and boundary conditions. In the proposed scheme, Laguerre polynomials are used together with an operational matrix and collocation method to obtain approximate solutions of the coupled system, so that our proposed model is converted into a system of algebraic equations which can be solved employing the Newton method. The solution profiles of the coupled system are presented graphically for different particular cases. The salient feature of the present article is finding the stability analysis of the proposed method and also the demonstration of the lower variation of solute concentrations with respect to the column length in the fractional-order system compared to the integer-order system. To show the higher efficiency, reliability, and accuracy of the proposed scheme, a comparison between the numerical results of Burger’s coupled system and its existing analytical result is reported. There are high compatibility and consistency between the approximate solution and its exact solution to a higher order of accuracy. The exhibition of error analysis for each case through tables and graphs confirms the super-linearly convergence rate of the proposed method.

Keywords: fractional coupled PDE, stability and convergence analysis, diffusion equation, Laguerre polynomials, spectral method

Procedia PDF Downloads 138

Authors: Debasis Sarkar

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Development of a Smart City would depend upon the development of its infrastructure in a smart way. Primarily based on the ideology of the fourth industrial revolution a Smart City project should have Smart governance, smart health care, smart building, smart transportation, smart mobility, smart energy, smart technology and smart citizen. Considering the Indian scenario of current state of cities in India, it has become very essential to decide the specific parameters which would govern the development of a Smart City project. It has been observed that there are significant parameters beyond Information and Communication Technology (ICT), which govern the development of a Smart City project. This paper is an attempt to identify the Critical Success Factors (CSF) which are significantly responsible for the development of a Smart City project in Western India. Responses to questionnaire survey were analyzed on basis of Likert scale. They were further critically evaluated with help of Factor Comparison Method (FCM) and Analytical Hierarchy Process (AHP). The project authorities need to incorporate Building Information Modeling (BIM) to make the smart city project more collaborative. To make the project more sustainable, use of flyash in the concrete used, reduced usage of cement and steel, use of alternate fuels like biodiesel is recommended.

Keywords: analytical hierarchical process, building information modeling, critical success factors, factor comparison method

Procedia PDF Downloads 242

Authors: Yiğit Gürler, Berkay Türkcan İmrağ, Taylan Güçkıran, İbrahim Şimşek, Alper Taşdemirci

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Paper honeycombs, which is a sandwich structure, consists of two liner faces and one paper honeycomb core. These materials are widely used in the packaging industry due to their low cost, low weight, good energy absorption capabilities and easy recycling properties. However, to provide maximum protection to the products in cases such as the drop of the packaged products, the mechanical behavior of these materials should be well known at the packaging design stage. In this study, the necessary input parameters for the modeling study were obtained by performing compression tests in the through-thickness and in-plane directions of paper-based honeycomb sandwich structures. With the obtained parameters, homogeneous and micro-mechanical numerical models were developed in the Ls-Dyna environment. The material card used for the homogeneous model is MAT_MODIFIED_HONEYCOMB, and the material card used for the micromechanical model is MAT_PIECEWISE_LINEAR_PLASTICITY. As a result, the effectiveness of homogeneous and micromechanical modeling approaches for paper-based honeycomb sandwich structure was investigated using force-displacement curves. Densification points and peak points on these curves will be compared.

Keywords: environmental packaging, mechanical characterization, Ls-Dyna, sandwich structure

Procedia PDF Downloads 187

Authors: Muhammad Jamil, Ning He, Aqib Mashood Khan, Munish Kumar Gupta

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Ti-6Al-4V has numerous applications in the medical, automobile, and aerospace industries due to corrosion resistivity, structural stability, and chemical inertness to most fluids at room temperature. These peculiar characteristics are beneficial for their application and present formidable challenges during machining. Machining of Ti-6Al-4V produces an elevated cutting temperature above 1000oC at dry conditions. This accelerates tool wear and reduces product quality. Therefore, there is always a need to employ sustainable/effective coolant/lubricant when machining such alloy. In this study, Finite Element Modeling (FEM) and experimental analysis when cutting Ti-6Al-4V under a distinctly developed dry ice mixed hybrid lubri-coolant are presented. This study aims to model the milling process of Ti-6Al-4V under a proposed novel hybrid lubri-coolant using different cutting speeds and feed per tooth DEFORM® software package was used to conduct the FEM and the numerical model was experimentally validated. A comparison of experimental and simulation results showed a maximum error of no more than 6% for all experimental conditions. In a nutshell, it can be said that the proposed model is effective in predicting the machining temperature precisely.

Keywords: friction coefficient, heat transfer, finite element modeling (FEM), milling Ti-6Al-4V

Procedia PDF Downloads 43

Authors: C. Bolakis, I. S. Karanasiou, D. Grbovic, G. Karunasiri, N. Uzunoglu

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A new approach for efficient detection of THz radiation in biomedical imaging applications is proposed. A double-layered absorber consisting of a 32 nm thick aluminum (Al) metallic layer, located on a glass medium (SiO2) of 1 mm thickness, was fabricated and used to design a fine-tuned absorber through a theoretical and finite element modeling process. The results indicate that the proposed low-cost, double-layered absorber can be tuned based on the metal layer sheet resistance and the thickness of various glass media taking advantage of the diversity of the absorption of the metal films in the desired THz domain (6 to 10 THz). It was found that the composite absorber could absorb up to 86% (a percentage exceeding the 50%, previously shown to be the highest achievable when using single thin metal layer) and reflect less than 1% of the incident THz power. This approach will enable monitoring of the transmission coefficient (THz transmission ‘’fingerprint’’) of the biosample with high accuracy, while also making the proposed double-layered absorber a good candidate for a microbolometer pixel’s active element. Based on the aforementioned promising results, a more sophisticated and effective double-layered absorber is under development. The glass medium has been substituted by diluted poly-si and the results were twofold: An absorption factor of 96% was reached and high TCR properties acquired. In addition, a generalization of these results and properties over the active frequency spectrum was achieved. Specifically, through the development of a theoretical equation having as input any arbitrary frequency in the IR spectrum (0.3 to 405.4 THz) and as output the appropriate thickness of the poly-si medium, the double-layered absorber retains the ability to absorb the 96% and reflects less than 1% of the incident power. As a result, through that post-optimization process and the spread spectrum frequency adjustment, the microbolometer detector efficiency could be further improved.

Keywords: bio-imaging, fine-tuned absorber, fingerprint, microbolometer

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Putul Haldar, Yogendra Singh, D. K. Paul

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Un-Reinforced Masonry (URM) infilled RC framed buildings are the most common construction practice for modern multi-storey buildings in India like many other parts of the world. Although the behavior and failure pattern of the global structure changes significantly due to infill-frame interaction, the general design practice is to treat them as non-structural elements and their stiffness, strength and interaction with frame is often ignored, as it is difficult to simulate. Indian Standard, like many other major national codes, does not provide any explicit guideline for modeling of infills. This paper takes a stock of controlling design provisions in some of the major national seismic design codes (BIS 2002; CEN 2004; NZS-4230 2004; ASCE-41 2007) to ensure the desired seismic performance of infilled frame. Most of the national codes on seismic design of buildings still lack in adequate guidelines on modeling and design of URM infilled frames results in variable assumption in analysis and design. This paper, using nonlinear pushover analysis, also presents the effect of one of such assumptions of conventional ‘simultaneous’ analysis procedure of infilled frame on the seismic performance of URM infilled RC frame buildings.

Keywords: URM infills, RC frame, seismic design codes, construction sequence of infilled frame

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Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

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Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

Procedia PDF Downloads 388

Authors: Elif Unveren, Ozlem Bozkurt

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Emotion processing happens when someone has a negative, stressful experience and gets over it in time, and it is a different experience for every person. As to look into emotion processing can be categorised by intensity, awareness, coordination, speed, accuracy and response. It may vary depending on people’s age, sex and conditions. Each emotion processing shows different activation patterns in different brain regions. Activation is significantly higher in the right frontal areas. The highest activation happens in extended frontotemporal areas during the processing of happiness, sadness and disgust. Those emotions also show widely disturbed differences and get produced earlier than anger and fear. For different occasions, listed variables may have less or more importance. A borderline personality disorder is a condition that creates an unstable personality, sudden mood swings and unpredictability of actions. According to a study that was made with healthy people and people who had BPD, there were significant differences in some categories of emotion processing, such as intensity, awareness and accuracy. According to another study that was made to show the emotional processing differences between puberty and was made for only females who were between the ages of 11 and 17, it was perceived that for different ages and hormone levels, different parts of the brain are used to understand the given task. Also, in the different study that was made for kids that were between the age of 4 and 15, it was observed that the older kids were processing emotion more intensely and expressing it to a greater extent. There was a significant increase in fear and disgust in those matters. To sum up, we can say that the activity of undertaking negative experiences is a unique thing for everybody for many different reasons.

Keywords: age, sex, conditions, brain regions, emotion processing

Procedia PDF Downloads 78

Authors: Chao-xun Liu, Shi-hong Lu

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In spite of its importance to the aerospace and automobile industries, little or no attention has been devoted to the accurate modeling of the ultrasonic shot peening (USP) process. It is therefore the purpose of this study to conduct finite element analysis of the process using a realistic multiple pin impacts model with the explicit solver of ABAQUS. In this paper, we research the effect of several key parameters on the residual stress distribution within the target, including impact velocity, incident angle, friction coefficient between pins and target and impact number of times were investigated. The results reveal that the impact velocity and impact number of times have obvious effect and impacting vertically could produce the most perfect residual stress distribution. Then we compare the results with the date in USP experiment and verify the exactness of the model. The analysis of the multiple pin impacts date reveal the relationships between peening process parameters and peening quality, which are useful for identifying the parameters which need to be controlled and regulated in order to produce a more beneficial compressive residual stress distribution within the target.

Keywords: ultrasonic shot peening, finite element, multiple pins, residual stress, numerical simulation

Procedia PDF Downloads 441

Authors: Freddy Patricio Moncayo-Matute, Pablo Gerardo Peña-Tapia, Vázquez-Silva Efrén, Paúl Bolívar Torres-Jara, Diana Patricia Moya-Loaiza, Gabriela Abad-Farfán

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This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure.

Keywords: surgical planning, additive manufacturing, rapid prototyping, fused deposition modeling, custom anatomical model

Procedia PDF Downloads 85

Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 139

Authors: K. A. Kemelov, Z. K. Maymekov, D. A. Sambaeva, W. Frenzel

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Benzo(a)pyrene is widespread carcinogenic and mutagenic environmental pollutant, which is formed in combustion processes of carbonaceous materials at high temperature and still health safety problem related benz(a)pyrene continues to remain actual. At the moment the mechanisms of formation of benzo(a)pyrene are not studied in detail, there is not concrete certain full scheme of synthesis of benzo(a)pyrene. Studies in this area are mainly dedicated to development of measuring tools and chemical reactions analyzes, or to obtain specific evidence of a large group of polycyclic aromatic hydrocarbons (PAHs). Consequently in this study we try to create physical and chemical model of oxidation and thermo destruction processes of benzo(a)pyrene, using critical thermodynamical parameters in order to estimate theoretical derivatives of benzo(a)pyrene and which conditions benzo(a)pyrene degraded into more harmful substances. According to this physical and chemical modeling of thermal destruction process of benzo(a)pyrene in wide ranges of change of temperature value were calculated. C20H12 - H2O-O2 system was taken for modeling of thermal destruction process of benzo(a)pyrene in order to establish distribution range of equilibrium structures and concentrations of molecules in a gas phase. Also technological ways of reduction of concentration of benzo(a)pyrene in a gas phase were supposed.

Keywords: benzo(a)pyrene, emission, PAH, thermodynamic parameters

Procedia PDF Downloads 286

Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

Procedia PDF Downloads 123

Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

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The aim of the study is to compare behaviorally and EEG reactions in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians during the recognition of syntax errors in native and foreign languages. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All participants completed a linguistic task, in which they had to find a syntax error in the written sentences. Russian participants completed the task in Russian and in English. Tuvinian and Yakut participants completed the task in Russian, English, and Tuvinian or Yakut, respectively. EEG’s were recorded during the solving of tasks. For Russian participants, EEG's were recorded using 128-channels. The electrodes were placed according to the extended International 10-10 system, and the signals were amplified using ‘Neuroscan (USA)’ amplifiers. For Tuvinians and Yakuts EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups 0.3-100 Hz analog filtering, sampling rate 1000 Hz were used. Response speed and the accuracy of recognition error were used as parameters of behavioral reactions. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The accuracy of solving tasks and response speed in Russians were higher for Russian than for English. The P300 amplitudes in Russians were higher for English; the P600 amplitudes in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages (Tuvinian and Yakut). However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. With Tuvinians, there were no differences in the P300 and P600 amplitudes and in cortical topology for Russian and Tuvinian, but there was a difference for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference and were reflected foreign language comprehension -while the Russian language comprehension was reflected native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, language comprehension, native and foreign languages, Siberian inhabitants

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Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

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Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine

Procedia PDF Downloads 194

Authors: M. N. Islam, B. Boswell, Y. R. Ginting

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The influence of canned cycles and cutting parameters on hole quality in cryogenic drilling has been investigated experimentally and analytically. A three-level, three-parameter experiment was conducted by using the design-of-experiment methodology. The three levels of independent input parameters were the following: for canned cycles—a chip-breaking canned cycle (G73), a spot drilling canned cycle (G81), and a deep hole canned cycle (G83); for feed rates—0.2, 0.3, and 0.4 mm/rev; and for cutting speeds—60, 75, and 100 m/min. The selected work and tool materials were aluminum 6061-6T and high-speed steel (HSS), respectively. For cryogenic cooling, liquid nitrogen (LN2) was used and was applied externally. The measured output parameters were the three widely used quality characteristics of drilled holes—diameter error, circularity, and surface roughness. Pareto ANOVA was applied for analyzing the results. The findings revealed that the canned cycle has a significant effect on diameter error (contribution ratio 44.09%) and small effects on circularity and surface finish (contribution ratio 7.25% and 6.60%, respectively). The best results for the dimensional accuracy and surface roughness were achieved by G81. G73 produced the best circularity results; however, for dimensional accuracy, it was the worst level.

Keywords: circularity, diameter error, drilling canned cycle, pareto ANOVA, surface roughness

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Authors: Nixon Kuruvila, H. V. Ravindra

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Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

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Authors: Dario Milani, Guido Morgenthal

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Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

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Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Bahar Ayhan

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The present paper is concerned with the numerical modeling of the inelastic behavior of the anisotropically damaged ductile materials, which are based on a generalized macroscopic theory within the framework of continuum damage mechanics. Kinematic decomposition of the strain rates into elastic, plastic and damage parts is basis for accomplishing the structure of continuum theory. The evolution of the damage strain rate tensor is detailed with the consideration of anisotropic effects. Helmholtz free energy functions are constructed separately for the elastic and inelastic behaviors in order to be able to address the plastic and damage process. Additionally, the constitutive structure, which is based on the standard dissipative material approach, is elaborated with stress tensor, a yield criterion for plasticity and a fracture criterion for damage besides the potential functions of each inelastic phenomenon. The finite element method is used to approximate the linearized variational problem. Stress and strain outcomes are solved by using the numerical integration algorithm based on operator split methodology with a plastic and damage (multiplicator) variable separately. Numerical simulations are proposed in order to demonstrate the efficiency of the formulation by comparing the examples in the literature.

Keywords: anisotropic damage, finite element method, plasticity, coupling

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Authors: Mohammed S. Razali, Kamel Khimeche, Dahah Hichem, Ammar Boudjellal, Djamel E. Kaderi, Nourddine Ramdani

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The use of additive manufacturing technologies has revolutionized various aspects of our daily lives. In particular, 3D printing has greatly advanced biomedical applications. While fused filament fabrication (FFF) technologies have made it easy to produce or prototype various medical devices, it is crucial to minimize the risk of contamination. New materials with antibacterial properties, such as those containing compounded silver nanoparticles, have emerged on the market. In a previous study, we prepared a newly sintered seashell filler (SSh) from bio-based seashells found along the Mediterranean coast using a suitable heat treatment process. We then prepared a series of polylactic acid (PLA) and polybutylene succinate (PBS) biocomposites filled with these SSh particles using a melt mixing technique with a twin-screw extruder to use them as feedstock filaments for 3D printing. The study consisted of two parts: evaluating the antibacterial activity of newly prepared biocomposites made of PLA and PBS reinforced with a sintered seashell in the first part and experimental and modeling analysis of the non-isothermal crystallization kinetics of these biocomposites in the second part. In the first part, the bactericidal activity of the biocomposites against three different bacteria, including Gram-negative bacteria such as (E. coli and Pseudomonas aeruginosa), as well as Gram-positive bacteria such as (Staphylococcus aureus), was examined. The PLA-based biocomposite containing 20 wt.% of SSh particles exhibited an inhibition zone with radial diameters of 8mm and 6mm against E. coli and Pseudo. Au, respectively, while no bacterial activity was observed against Staphylococcus aureus. In the second part, the focus was on investigating the effect of the sintered seashell filler particles on the non-isothermal crystallization kinetics of PLA and PBS 3D-printing composite materials. The objective was to understand the impact of the filler particles on the crystallization mechanism of both PLA and PBS during the cooling process of a melt-extruded filament in (FFF) to manage the dimensional accuracy and mechanical properties of the final printed part. We conducted a non-isothermal melt crystallization kinetic study of a series of PLA-SS and PBS-SS composites using differential scanning calorimetry at various cooling rates. We analyzed the obtained kinetic data using different crystallization kinetic models such as modified Avrami, Ozawa, and Mo's methods. Dynamic mode describes the relative crystallinity as a function of temperature; it found that time half crystallinity (t1/2) of neat PLA decreased from 17 min to 7.3 min for PLA+5 SSh and the (t1/2) of virgin PBS was reduced from 3.5 min to 2.8 min for the composite containing 5wt.% of SSh. We found that the coated SS particles with stearic acid acted as nucleating agents and had a nucleation activity, as observed through polarized optical microscopy. Moreover, we evaluated the effective energy barrier of the non-isothermal crystallization process using the Iso conversional methods of Flynn-Wall-Ozawa (F-W-O) and Kissinger-Akahira-Sunose (K-A-S). The study provides significant insights into the crystallization behavior of PLA and PBS biocomposites.

Keywords: avrami model, bio-based reinforcement, dsc, gram-negative bacteria, gram-positive bacteria, isoconversional methods, non-isothermal crystallization kinetics, poly(butylene succinate), poly(lactic acid), antbactirial activity

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Authors: S. S. Ghodsi, M. H. Mehrabi, Zainah Ibrahim, Meldi Suhatril

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This research examines the performance of a hybrid passive control device for enhancing the seismic response of steel frame structures. The device design comprises a damper which employs a viscoelastic material to control both shear and axial strain. In the design, energy is dissipated through the shear strain of a two-layer system of viscoelastic pads which are located between steel plates. In addition, viscoelastic blocks have been included on either side of the main shear damper which obtains compressive strains in the viscoelastic blocks. These dampers not only dissipate energy but also increase the stiffness of the steel frame structure, and the degree to which they increase the stiffness may be controlled by the size and shape. In this research, the cyclical behavior of the damper was examined both experimentally and numerically with finite element modeling. Cyclic loading results of the finite element modeling reveal fundamental characteristics of this hybrid viscoelastic damper. The results indicate that incorporating a damper of the design can significantly improve the seismic performance of steel frame structures.

Keywords: cyclic loading, energy dissipation, hybrid damper, passive control system, viscoelastic damper

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Authors: Seyed Amin Vakili, Sahar Sadat Vakili, Seyed Ehsan Vakili, Nader Abdoli Yazdi

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The main purpose of this paper is to present the Modified Newmark Method as a method of non-linear frame analysis by considering the effect of the axial load (second order analysis). The discussion will be restricted to plane frameworks containing a constant cross-section for each element. In addition, it is assumed that the frames are prevented from out-of-plane deflection. This part of the investigation is performed to generalize the established method for the assemblage structures such as frameworks. As explained, the governing differential equations are non-linear and cannot be formulated easily due to unknown axial load of the struts in the frame. By the assumption of constant axial load, the governing equations are changed to linear ones in most methods. Since the modeling and the solutions of the non-linear form of the governing equations are cumbersome, the linear form of the equations would be used in the established method. However, according to the ability of the method to reconsider the minor omitted parameters in modeling during the solution procedure, the axial load in the elements at each stage of the iteration can be computed and applied in the next stage. Therefore, the ability of the method to present an accurate approach to the solutions of non-linear equations will be demonstrated again in this paper.

Keywords: nonlinear, stability, buckling, modified newmark method

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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