Search results for: structure prediction

Authors: Ali Reza Ghanbarnezhad Ghazvini, Seyyed Hamid Reza Mosayyebi

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In recent years, an earthquake has occurred approximately every five years in certain regions of Iran. To mitigate the impact of these seismic events, it is crucial to identify and thoroughly assess the vulnerability of buildings and infrastructure, ensuring their safety through principled reinforcement. By adopting new methods of risk assessment, we can effectively reduce the potential risks associated with future earthquakes. In our research, we have observed that the coefficient of behavior in the fourth chapter is 1.65 for the initial structure and 1.72 for the Superframe structure. This indicates that the Superframe structure can enhance the strength of the main structural members by approximately 10% through the utilization of super beams. Furthermore, based on the comparative analysis between the two structures conducted in this study, we have successfully designed a stronger structure with minimal changes in the coefficient of behavior. Additionally, this design has allowed for greater energy dissipation during seismic events, further enhancing the structure's resilience to earthquakes. By comprehensively examining and reinforcing the vulnerability of buildings and infrastructure, along with implementing advanced risk assessment techniques, we can significantly reduce casualties and damages caused by earthquakes in Iran. The findings of this study offer valuable insights for civil engineering professionals in the field of structural engineering, aiding them in designing safer and more resilient structures.

Keywords: modal pushover analysis, response modification factor, high-strength concrete, concrete shear walls, high-rise building

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: Noemia Gomes de Mattos de Mesquita, José Eduardo Ferreira de Oliveira, Arimatea Quaresma Ferraz

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Stops to exchange cutting tool, to set up again the tool in a turning operation with CNC or to measure the workpiece dimensions have a direct influence on production. The premature removal of the cutting tool results in high cost of machining since the parcel relating to the cost of the cutting tool increases. On the other hand, the late exchange of cutting tool also increases the cost of production because getting parts out of the preset tolerances may require rework for its use when it does not cause bigger problems such as breaking of cutting tools or the loss of the part. Therefore, the right time to exchange the tool should be well defined when wanted to minimize production costs. When the flank wear is the limiting tool life, the time predetermination that a cutting tool must be used for the machining occurs within the limits of tolerance can be done without difficulty. This paper aims to show how the life of the cutting tool can be calculated taking into account the cutting parameters (cutting speed, feed and depth of cut), workpiece material, power of the machine, the dimensional tolerance of the part, the finishing surface, the geometry of the cutting tool and operating conditions of the machine tool, once known the parameters of Taylor algebraic structure. These parameters were raised for the ABNT 1038 steel machined with cutting tools of hard metal.

Keywords: machining, productions, cutting condition, design, manufacturing, measurement

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Jatziri Y. Moreno-Martinez, Arturo Galvan, Xavier Chavez Cardenas, Hiram Arroyo

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Several methods have been utilized to study the prediction of cracking of concrete structural under loading. The finite element analysis is an alternative that shows good results. The aim of this work was the numerical study of the width crack in reinforced concrete beams with dapped ends, these are frequently found in bridge girders and precast concrete construction. Properly restricting cracking is an important aspect of the design in dapped ends, it has been observed that the cracks that exceed the allowable widths are unacceptable in an aggressive environment for reinforcing steel. For simulating the crack width, the discrete crack approach was considered by means of a Cohesive Zone (CZM) Model using a function to represent the crack opening. Two cases of dapped-end were constructed and tested in the laboratory of Structures and Materials of Engineering Institute of UNAM. The first case considers a reinforcement based on hangers as well as on vertical and horizontal ring, the second case considers 50% of the vertical stirrups in the dapped end to the main part of the beam were replaced by an equivalent area (vertically projected) of diagonal bars under. The loading protocol consisted on applying symmetrical loading to reach the service load. The models were performed using the software package ANSYS v. 16.2. The concrete structure was modeled using three-dimensional solid elements SOLID65 capable of cracking in tension and crushing in compression. Drucker-Prager yield surface was used to include the plastic deformations. The reinforcement was introduced with smeared approach. Interface delamination was modeled by traditional fracture mechanics methods such as the nodal release technique adopting softening relationships between tractions and the separations, which in turn introduce a critical fracture energy that is also the energy required to break apart the interface surfaces. This technique is called CZM. The interface surfaces of the materials are represented by a contact elements Surface-to-Surface (CONTA173) with bonded (initial contact). The Mode I dominated bilinear CZM model assumes that the separation of the material interface is dominated by the displacement jump normal to the interface. Furthermore, the opening crack was taken into consideration according to the maximum normal contact stress, the contact gap at the completion of debonding, and the maximum equivalent tangential contact stress. The contact elements were placed in the crack re-entrant corner. To validate the proposed approach, the results obtained with the previous procedure are compared with experimental test. A good correlation between the experimental and numerical Load-Displacement curves was presented, the numerical models also allowed to obtain the load-crack width curves. In these two cases, the proposed model confirms the capability of predicting the maximum crack width, with an error of ± 30 %. Finally, the orientation of the crack is a fundamental for the prediction of crack width. The results regarding the crack width can be considered as good from the practical point view. Load-Displacement curve of the test and the location of the crack were able to obtain favorable results.

Keywords: cohesive zone model, dapped-end beams, discrete crack approach, finite element analysis

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Authors: Ali Essam El Shazly

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The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: A. Kudrev

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The duplex Poly(A)-Poly(U) denaturation in an aqueous solutions in mixtures with the tetracationic MeTMPyP4 (Me = 2H, Zn(II); TMPyP4 is 5,10,15,20-tetrakis(N-methylpyridinium-4-yl)porphyrin), was investigated by monitoring the changes in the UV-Vis absorbance spectrum with increasing temperatures from 20°С to 70°С (рН 7.0, I=0.15M). The absorbance data matrices were analyzed with a versatile chemometric procedure that provides the melting profile (distribution of species) and the pure spectrum for each chemical species present along the heating experiment. As revealed by the increase of Tm, the duplex structure was stabilized by these porphyrins. The values of stabilization temperature ΔTm in the presence of these porphyrins are relatively large, 1.2-8.4 °C, indicating that the porphyrins contribute differently in stabilizing the duplex Poly(A)-Poly(U) structure. Remarkable is the fact that the porphyrin TMPyP4 was less effective in the stabilization of the duplex structure than the metalloporphyrin Zn(X)TMPyP4 which suggests that metallization play an important role in porphyrin-RNA binding. Molecular Dynamics Simulations has been used to illustrate melting of the duplex dsRNA bound with a porphyrin molecule.

Keywords: melting, Poly(A)-Poly(U), TMPyP4, Zn(X)TMPyP4

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Authors: Jaime Carpio-García, Elena Blanco-Fernández, Jorge Rodríguez-Hernández, Daniel Castro-Fresno

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Geosynthetic mechanical behavior vs temperature or vs aging has been widely studied independently during the last years, both in laboratory and in outdoor conditions. This paper studies this behavior deeper, considering that geosynthetics have to perform adequately at different outdoor temperatures once they have been subjected to a certain degree of aging, and also considering the different geosynthetic structures made of the same material. This combining effect has been not considered so far, and it is important to ensure the performance of geosynthetics, especially where high temperatures are expected. In order to fill this gap, six commercial geosynthetics with different internal structures made of polypropylene (PP), high density polyethylene (HDPE), bitumen and polyvinyl chloride (PVC), or even a combination of some of them have been mechanically tested at mild temperature (20ºC or 23ºC) and at warm temperature (45ºC) before and after specific exposition to air at standardized high temperature in order to simulate 25 years of aging due to oxidation. Besides, for 45ºC tests, an innovative heating system during test for high deformable specimens is proposed. The influence of the combining effect of aging, structure and temperature in the product behavior have been analyzed and discussed, concluding that internal structure is more influential than aging in the mechanical behavior of a geosynthetic versus temperature.

Keywords: geosynthetics, mechanical behavior, temperature, aging, internal structure

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Authors: Shamshiri Mitra, Abedi Rahim

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This paper investigates corporate investment behavior and its relationship with ownership structure and financial leverage for the listed company of Tehran stock exchange during 2008-2012. The results show that the concentration of ownership has s significant positive effect on corporate investment. The results for the kind of major owners show that institutional ownership had a positive significant effect and state and individual ownership had negative significant effects on the corporate investment but the effect of corporate ownership was not significant. Furthermore the effect of financial leverage was negative and significant.

Keywords: corporate investment behavior, financial leverage, ownership structure corporate investment behavior

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Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

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Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

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Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: parameterization, response surface, structure optimization, pressure hull

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Authors: Heba Abdelmotaal

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This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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Authors: M. Reyes, R. Sastre, P. Gabana, F. V. Tinaut

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In this work, an optical characterization of the ethanol-air laminar combustion is presented in order to investigate the origin of the instabilities developed during the combustion, the onset of the cellular structure and the laminar burning velocity. Experimental tests of ethanol-air have been developed in an optical cylindrical constant volume combustion bomb equipped with a Schlieren technique to record the flame development and the flame front surface wrinkling. With this procedure, it is possible to obtain the flame radius and characterize the time when the instabilities are visible through the cell's apparition and the cellular structure development. Ethanol is an aliphatic alcohol with interesting characteristics to be used as a fuel in Internal Combustion Engines and can be biologically synthesized from biomass. Laminar burning velocity is an important parameter used in simulations to obtain the turbulent flame speed, whereas the flame front structure and the instabilities developed during the combustion are important to understand the transition to turbulent combustion and characterize the increment in the flame propagation speed in premixed flames. The cellular structure is spontaneously generated by volume forces, diffusional-thermal and hydrodynamic instabilities. Many authors have studied the combustion of ethanol air and mixtures of ethanol with other fuels. However, there is a lack of works that investigate the instabilities and the development of a cellular structure in ethanol flames, a few works as characterized the ethanol-air combustion instabilities in spherical flames. In the present work, a parametrical study is made by varying the fuel/air equivalence ratio (0.8-1.4), initial pressure (0.15-0.3 MPa) and initial temperature (343-373K), using a design of experiments type I-optimal. In reach mixtures, it is possible to distinguish the cellular structure formed by the hydrodynamic effect and by from the thermo-diffusive. Results show that ethanol-air flames tend to stabilize as the equivalence ratio decreases in lean mixtures and develop a cellular structure with the increment of initial pressure and temperature.

Keywords: ethanol, instabilities, premixed combustion, schlieren technique, cellularity

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Authors: Omar Qaftan

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Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

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Authors: Seokyoon Moon, Yun-Ho Ahn, Heejoong Kim, Sujin Hong, Yunseok Lee, Youngjune Park

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Gas hydrate is a non-stoichiometric crystalline compound consisting of host water-framework and low molecular weight guest molecules. Small gaseous molecules such as CH₄, CO₂, and N₂ can be captured in the host water framework lattices of the gas hydrate with specific temperature and pressure conditions. The three well-known crystal structures of structure I (sI), structure II (sII), and structure H (sH) are determined by the size and shape of guest molecules. In this study, we measured the phase equilibria of binary (2,2-dimethyl-1-propanol + CO₂, CH₄, N₂) hydrates to explore their fundamental thermodynamic characteristics. We identified the structure of the binary gas hydrate by employing synchrotron high-resolution powder diffraction (HRPD), and the guest distributions in the lattice of gas hydrate were investigated via dispersive Raman and ¹³C solid-state nuclear magnetic resonance (NMR) spectroscopies. The end-to-end distance of 2,2-dimethyl-1-propanol was calculated to be 7.76 Å, which seems difficult to be enclathrated in large cages of sI or sII. However, due to the flexibility of the host water framework, binary hydrates of sI or sII types can be formed with the help of small gas molecule. Also, the synchrotron HRPD patterns revealed that the binary hydrate structure highly depends on the type of help gases; a cubic Fd3m sII hydrate was formed with CH₄ or N₂, and a cubic Pm3n sI hydrate was formed with CO₂. Interestingly, dispersive Raman and ¹³C NMR spectra showed that the unique tuning phenomenon occurred in binary (2,2-dimethyl-1-propanol + CO₂) hydrate. By optimizing the composition of NPA, we can achieve both thermodynamic stability and high CO₂ storage capacity for the practical application to CO₂ capture.

Keywords: clathrate, gas hydrate, neopentyl alcohol, CO₂, tuning phenomenon

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Authors: Alexander Pesin, Denis Pustovoytov, Mikhail Sverdlik

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Materials with ultrafine-grained structure and unique physical and mechanical properties can be obtained by methods of severe plastic deformation, which include processes of asymmetric rolling (AR). Asymmetric rolling is a very effective way to create ultrafine-grained structures of metals and alloys. Since the asymmetric rolling is a continuous process, it has great potential for industrial production of ultrafine-grained structure sheets. Basic principles of asymmetric rolling are described in detail in scientific literature. In this work finite element modeling of asymmetric rolling and metal forming processes in multiroll gauge was performed. Parameters of the processes which allow achieving significant values of shear strain were defined. The results of the study will be useful for the research of the evolution of ultra-fine metal structure in asymmetric rolling.

Keywords: asymmetric rolling, equivalent strain, FEM, multiroll gauge, profile, severe plastic deformation, shear strain, sheet

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Authors: Tasir Khan, Yejuan Wang

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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.

Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: M. Zain, Thaung H. Aung, Naveed Anwar

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During the service life, a structure may experience extreme loading conditions. The current study proposes a new methodology that covers the effect of uncertainty involved in gravity loadings on key structural elements of new and complex structures by emphasizing on a very realistic assumption that allows the 'Performance-Based Assessment' to be executed on the structure against the gravity loadings. The methodology does not require the complete removal of an element, instead, it permits the incremental reduction in the capacity of key structural elements and preserves the same stiffness of the member in each case of capacity loss. To demonstrate the application of the proposed methodology, a 13 story complex structure is selected that comprises of a diverse structural configuration. The results ensure the structural integrity against the applied gravity loadings, as well as the effectiveness of the proposed methodology.

Keywords: force-deformation relationship, gravity loading, incremental capacity reduction, multi-linear plastic link element, SAP2000, stiffness

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Authors: Lexi Li, Vanessa H. K. Pang

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This study aims to demonstrate how native and learner corpora can be used to enhance modal verb treatment in EFL textbooks in mainland China. It contributes to a corpus-informed and learner-centered design of grammar presentation in EFL textbooks that enhances the authenticity and appropriateness of textbook language for target learners. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the 'secondary school' section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was analyzed in terms of the use (distributional features, semantic functions, and co-occurring constructions) and the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The analysis of distribution indicates several discrepancies between the textbook corpus and BNCS2014. The first four most frequent modal verbs in BNCS2014 are can, would, will, could, while can, will, should, could are the top four in the textbooks. Most strikingly, there is an unusually high proportion of can (41.1%) in the textbooks. The results on different meanings shows that will, would and must are the most problematic. For example, for will, the textbooks contain 20% more occurrences of 'volition' and 20% less of 'prediction' than those in BNCS2014. Regarding co-occurring structures, the textbooks over-represented the structure 'modal +do' across the nine modal verbs. Another major finding is that the structure of 'modal +have done' that frequently co-occur with could, would, should, and must is underused in textbooks. Besides, these four modal verbs are the most difficult for learners, as the error analysis shows. This study demonstrates how the synergy of native and learner corpora can be harnessed to improve EFL textbook presentation of modal verbs in a way that textbooks can provide not only authentic language used in natural discourse but also appropriate design tailed for the needs of target learners.

Keywords: English as Foreign Language, EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: H. Nikzad, S. Yoshitomi

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In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures

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Authors: Gelu Varghese, Khizer Saeed

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Biodiesel is as a mixture of mono-alkyl esters of long chain fatty acids derived from vegetable oils or animal fats. Recent studies in the literature suggest that end property of biodiesel such as its oxidative stability (OS) is highly influenced by the structure and composition of its alkyl esters than by environmental conditions. The structure and composition of these long chain fatty acid components have been also associated with trends in Cetane number, heat of combustion, cold flow properties viscosity, and lubricity. In the present work, detailed investigation has been carried out to decouple and correlate the fatty acid structure indices of biodiesel such as degree of unsaturation, chain length, double bond orientation, and composition with its oxidative stability. Measurements were taken using the EN14214 established Rancimat oxidative stability test method (EN141120). Firstly, effects of the degree of unsaturation, chain length and bond orientation were tested for the pure fatty acids to establish their oxidative stability. Results for pure Fatty acid show that Saturated FAs are more stable than unsaturated ones to oxidation; superior oxidative stability can be achieved by blending biodiesel fuels with relatively high in saturated fatty acid contents. A lower oxidative stability is noticed when a greater quantity of double bonds is present in the methyl ester. A strong inverse relationship with the number of double bonds and the Rancimat IP values can be identified. Trans isomer Methyl elaidate shows superior stability to oxidation than its cis isomer methyl oleate (7.2 vs. 2.3). Secondly, the effects of the variation in the composition of the biodiesel were investigated and established. Finally, biodiesels with varying structure and composition were investigated and correlated.

Keywords: biodiesel, fame, oxidative stability, fatty acid structure, acid composition

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Authors: Amit Saraswat, Ruchi Tewari

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Purpose: The research paper aims at understanding the alignment of business and IT in the Indian context and the business value attached to such an alignment. Methodology: The study is conducted in two stages. Stage one: Bibliographic research was conducted to evolve the parameters for defining alignment. Stage two: Evolving a model for strategic alignment to conduct an empirical study. The model is defined in terms of four fundamental domains of strategic management choice – business strategy, information strategy, organizational structure, and information technology structure. A survey through a questionnaire was conducted across organizations from 4 different industries and Structure Equation Modelling (SEM) technique is used for validating the model. Findings: In the Indian scenario all the subscales of alignment could not be validated. It could be validated that organizational strategy impacts information strategy and information technology structure. Research Limitations: The study is limited to the Indian context. Business IT alignment may be culture dependent so further research is required to validate the model in other cultures. Originality/Value: In the western world several models of alignment of business strategy and information systems is available but they do not measure the extent of alignment which the current study in the Indian context. Findings of the study can be used by managers in strategizing and understanding their business and information systems needs holistically and cohesively leading to efficient use of resources and output.

Keywords: business strategy, information technology (IT), business IT alignment, SEM

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Authors: Houmame Benbouali

Abstract:

This paper introduces the design, analysis, tests and application of a new isolation system used in irregular structure, also briefly introduces the recent research, and development on seismic isolation of civil buildings in China. A very large platform (2 stories RC frame) with plane size 1500m wide and 2000m long was built to cover the city railway communication hub area. About 50 isolation house buildings (9 stories RC frame) with 480,000 M2 were built on the top floor of platform. A new advanced isolation system named Storied-Isolation was used to ensure the seismic safety for this irregular structure with the largest isolation house building area in the world. This new isolation system has been used widely in China. There are over 400 buildings with seismic isolation have been built in China until 2003. This paper will introduce the recent research, and development on seismic isolation of civil buildings in China, including the tendency of application on seismic isolation, different isolation systems, different design level being used, design codes, application status and examples of application. Also the paper makes discussion of some problems on the future development of seismic isolation in China.

Keywords: civil buildings, floor, irregular structure, seismic isolation

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Authors: I. Shuro

Abstract:

The crystal structure of Tin Sulfide prepared by certain chemical methods is investigated using High-Resolution Transmission Electron Microscopy (HRTEM), Scanning Electron Microscopy (SEM), and X-ray diffraction (XRD) methods. An anomalous HRTEM Fast Fourier Transform (FFT) exhibited a central scatter of diffraction spots, which is surrounded by secondary clusters of spots arranged in a hexagonal pattern around the central cluster was observed. FFT analysis has revealed a long lattice parameter and mostly viewed along a hexagonal axis where there many columns of atoms slightly displaced from one another. This FFT analysis has revealed that the metal sulfide has a long-range order interwoven chain of atoms in its crystal structure. The observed crystalline structure is inconsistent with commonly observed FFT patterns of chemically synthesized Tin Sulfide nanocrystals and thin films. SEM analysis showed the morphology of a myriad of multi-shaped crystals ranging from hexagonal, cubic, and spherical micro to nanostructured crystals. This study also investigates the presence of quasi-crystals as reflected by the presence of mixed local symmetries.

Keywords: fast fourier transform, high resolution transmission electron microscopy, tin sulfide, crystalline structure

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Authors: J. Kundrák, I. Sztankovics, K. Gyáni

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In addition to the increase of the material removal rate or surface rate, or the improvement of the surface quality, which are the main aims of the development of manufacturing technology, a growing number of other manufacturing requirements have appeared in the machining of workpiece surfaces. Among these, it is becoming increasingly dominant to generate a surface topography in finishing operations which meet more closely the needs of operational requirements. These include the examination of the surface periodicity and/or ensuring that the twist structure values are within the limits (or even preventing its occurrence) in specified cases such as on the sealing surfaces of rotating shafts or on the inside working surfaces of needle roller bearings. In the view of the measurement, the twist has different parameters from surface roughness, which must be determined for the machining procedures. Therefore in this paper the alteration of the theoretical values of the parameters determining twist structure are studied as a function of the kinematic properties.

Keywords: kinematic parameters, rotational turning, surface topography, twist structure

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Authors: S. Ghoudelbourk, A. Omeiri, D. Dib, H. Cheghib

Abstract:

This paper shows that we can improve the performance of the auto-adjustable electric machines if a fractional dynamic is considered in the algorithm of the controlling order. This structure is particularly interested in the separate control of active and reactive power of the double-fed induction generator (DFIG) of wind power conversion chain. Fractional regulators are used in the regulation of chain of powers. Knowing that, usually, the source of DFIG is provided by converters through controlled rectifiers, all this system makes the currents of lines strongly polluted that can have a harmful effect for the connected loads and sensitive equipment nearby. The solution to overcome these problems is to replace the power of the rotor DFIG by multilevel inverters supplied by PV which improve the THD. The structure of the adopted adjustment is tested using Matlab/Simulink and the results are presented and analyzed for a variable wind.

Keywords: DFIG, fractional regulator, multilevel inverters, PV

Procedia PDF Downloads 395