Search results for: hardness prediction

Authors: Mohamed K. El-Fawkhry, Ahmed Shash, Ahmed Ismail Zaki Farahat, Sherif Ali Abd El Rahman, Taha Mattar

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High-carbon, silicon-rich steels are commonly suggested to obtain very fine bainitic microstructure at low temperature ranged from 200 to 300°C. Thereby, the resulted microstructure consists of slender of bainitic-ferritic plates interwoven with retained austenite. The advanced strength and ductility package of this steel is much dependent on the fineness of bainitic ferrite, as well as the retained austenite phase. In this article, Aluminum to Silicon ratio, and the isothermal transformation temperature have been adopted to obtain ultra high strength high carbon steel. Optical and SEM investigation of the produced steels have been performed. XRD has been used to track the retained austenite development as a result of the change in the chemical composition of developed steels and heat treatment process. Mechanical properties in terms of hardness and microhardness of obtained phases and structure were investigated. It was observed that the increment of aluminum to silicon ratio has a great effect in promoting the bainitic transformation, in tandem with improving the stability and the fineness of retained austenite. Such advanced structure leads to enhancement in the whole mechanical properties of the high carbon steel.

Keywords: high-carbon steel, silicon-rich steels, fine bainitic microstructure, retained austenite, isothermal transformation

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Authors: Muhammad Zaman Shakir, Mingfa Yao, Zohaib Iqbal

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This study proposed four Jet fuel surrogate (S1, S2 S3, and 4) with careful selection of seven large hydrocarbon fuel components, ranging from C₉-C₁₆ of higher molecular weight and higher boiling point, adapting the standard molecular distribution size of the actual jet fuel. The surrogate was composed of seven components, including n-propyl cyclohexane (C₉H₁₈), n- propylbenzene (C₉H₁₂), n-undecane (C₁₁H₂₄), n- dodecane (C₁₂H₂₆), n-tetradecane (C₁₄H₃₀), n-hexadecane (C₁₆H₃₄) and iso-cetane (iC₁₆H₃₄). The skeletal jet fuel surrogate reaction mechanism was developed by two approaches, firstly based on a decoupling methodology by describing the C₄ -C₁₆ skeletal mechanism for the oxidation of heavy hydrocarbons and a detailed H₂ /CO/C₁ mechanism for prediction of oxidation of small hydrocarbons. The combined skeletal jet fuel surrogate mechanism was compressed into 128 species, and 355 reactions and thereby can be used in computational fluid dynamics (CFD) simulation. The extensive validation was performed for individual single-component including ignition delay time, species concentrations profile and laminar flame speed based on various fundamental experiments under wide operating conditions, and for their blended mixture, among all the surrogate, S1 has been extensively validated against the experimental data in a shock tube, rapid compression machine, jet-stirred reactor, counterflow flame, and premixed laminar flame over wide ranges of temperature (700-1700 K), pressure (8-50 atm), and equivalence ratio (0.5-2.0) to capture the properties target fuel Jet-A, while the rest of three surrogate S2, S3 and S4 has been validated for Shock Tube ignition delay time only to capture the ignition characteristic of target fuel S-8 & GTL, IPK and RP-3 respectively. Based on the newly proposed HyChem model, another four surrogate with similar components and composition, was developed and parallel validations data was used as followed for previously developed surrogate but at high-temperature condition only. After testing the mechanism prediction performance of surrogates developed by the decoupling methodology, the comparison was done with the results of surrogates developed by the HyChem model. It was observed that all of four proposed surrogates in this study showed good agreement with the experimental measurements and the study comes to this conclusion that like the decoupling methodology HyChem model also has a great potential for the development of oxidation mechanism for heavy alkanes because of applicability, simplicity, and compactness.

Keywords: computational fluid dynamics, decoupling methodology Hychem, jet fuel, surrogate, skeletal mechanism

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Authors: Meltem Bolluk, Ismail Duman

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Boron exhibits the properties of high melting temperature (2273K to 2573 K), high hardness (Mohs: 9,5), low density (2,340 g/cm3), high chemical resistance, high strength, and semiconductivity (band gap:1,6-2,1 eV). These superior properties enable to use it in several high-tech areas from electronics to nuclear industry and especially in high temperature metallurgy. Amorphous boron and crystalline boron have different application areas. Amorphous boron powder (directly amorphous and/or α-rhombohedral) is preferred in rocket firing, airbag inflating and in fabrication of superconducting MgB2 wires. The conventional ways to produce elemental boron with a purity of 85 pct to 95 prc are metallothermic reduction, fused salt electrolysis and mechanochemical synthesis; but the only way to produce high-purity boron powders is Chemical Vapour Deposition (Hot Surface CVD). In this study; amorphous boron powders with a minimum purity of 99,9 prc were synthesized in quartz tubes using BCl3-H2 gas mixture by CVD. Process conditions based on temperature and gas flow rate were determined. Thermodynamical interpretation of BCl3-H2 system for different temperatures and molar rates were performed using Fact Sage software. The characterization of powders was examined by using Xray diffraction (XRD), Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM), Stereo Microscope (SM), Helium gas pycnometer analysis. The purities of final products were determined by titration after lime fusion.

Keywords: amorphous boron, CVD, powder production, powder characterization

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Authors: Ilaria Manca, Ilaria Manca, Francesca Pettinau, Ignazia Mocci, Elisabetta M. Usai, Barbara Pittau

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Lamotrigine is a phenyltriazine used in the treatment of epilepsy and bipolar disorder type I. The purpose of this study was to test and compare various solid forms of immediate release (IR) lamotrigine products, at different strenghts, in order to study their disaggregation and dissolution behavior. IR products are designed to release their active substance promptly after administration. Concentration of hydrochloric acid in gastric juice is about 0.1-0.001 M, so FDA (Food and Drug Administration) recommends, for lamotrigine regular tablets, dissolution tests in HCl 0.1 M.Toinvestigate the pH dependency of drug release in the entire gastrointestinal tract, we worked at two additional media with different pH values (4.5 and 6.8), that reflect conditions in it. To afford acceptable dissolution rates, tablets must disintegrate. Disaggregation of constituent particles increases the surface area and substantially increases the dissolution rate. For this reason availability of an active substance from tablets depends on its ability to disintegrate fast in dissolution media. pH of gastrointestinal fluid affects drug absorption by conditioning its solubility and dissolution, but also tablet disintegration may be influenced by it. To obtain information about the quantitative relationship between different mixture components, Nuclear Magnetic Resonance (NMR) spectroscopy was used. We also investigate tablet hardness. The investigation carried out confirms pH 1.2 as the ideal environment for the immediate availability of the active substance.

Keywords: dissolution, disaggregation, Lamotrigine, bioequivalence

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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Authors: F. Pari, E. Fathiazar, T. Hashemi, M. Pari

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The present study aimed to examine the role of self-efficacy and school belonging in the academic achievement of Tabriz high school students in grade 11. Therefore, using a random cluster method, 377 subjects were selected from the whole students of Tabriz high schools. They filled in the School Belonging Questionnaire (SBQ) and General Self-Efficacy Scale. Data were analyzed using correlational as well as multiple regression methods. Findings demonstrate self-efficacy and school belonging have significant roles in the prediction of academic achievement. On the other hand, the results suggest that considering the gender variable there is no significant difference between self-efficacy and school belonging. On the whole, cognitive approaches could be effective in the explanation of academic achievement.

Keywords: school belonging, self-efficacy, academic achievement, high school

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

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Authors: G. A. Adamu, M. S. Sallau, S. O. Idris, E. B. Agbaji

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Drinking water is supplied to Danbatta, Makoda and some parts of Minjibir local government areas of Kano State from the surface water of Thomas Reservoir. The present land use in the catchment area of the reservoir indicates high agricultural activities, fishing, as well as domestic and small scale industrial activities. To study and monitor the quality of surface and drinking water of the area, water samples were collected from the reservoir, treated water at the treatment plant and potable water at the consumer end in three seasons November - February (cold season), March - June (dry season) and July - September (rainy season). The samples were analyzed for physical and chemical parameters, pH, temperature, total dissolved solids (TDS), conductivity, turbidity, total hardness, suspended solids, total solids, colour, dissolved oxygen (DO), biological oxygen demand (BOD), chloride ion (Cl^-) nitrite (NO₂^-), nitrate (NO₃^-), chemical oxygen demand (COD) and phosphate (PO₄^3-). The higher values obtained in some parameters with respect to the acceptable standard set by World Health Organization (WHO) and Nigerian Industrial Standards (NIS) indicate the pollution of both the surface and drinking water. These pollutants were observed to have a negative impact on water quality in terms of eutrophication, largely due to anthropogenic activities in the watershed.

Keywords: surface water, drinking water, water quality, pollution, Thomas reservoir, Kano

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Authors: Ikenna Charles Onyema, Tolut Prince Bako

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A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August - December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 °C, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), conductivity (44738.75 ± 6262.76 µS/cm), total dissolved solids (29236.71 ± 4273.30 mg/L), salinity (27.11 ± 3.91 ‰), alkalinity (126.99 ± 42.81 mg/L) and chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for acidity (2.34 ± 0.63 mg/L), total hardness (4711.98 ± 691.50 mg/L), phosphate (1.1 ± 0.78 mg/L), sulphate (2601.99 ± 447.04 mg/L) and nitrate (0.12 ± 0.06 mg/L). Values for total suspended solids and biological oxygen demand values were low (<1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, lighthouse beach, microalgae

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar

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This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model

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Authors: Selma Bouasria, Mahi Abdelkader, Abbès Azzi, Herouz Keltoum

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This paper reports concept was used into the computational fluid dynamics (CFD) code cfx through user-defined functions to assess ventilation efficiency inside (forced-ventilation local). CFX is a simulation tool which uses powerful computer and applied mathematics, to model fluid flow situations for the prediction of heat, mass and momentum transfer and optimal design in various heat transfer and fluid flow processes to evaluate thermal comfort in a room ventilated (highly-glazed). The quality of the solutions obtained from CFD simulations is an effective tool for predicting the behavior and performance indoor thermo-aéraulique comfort.

Keywords: ventilation, thermal comfort, CFD, indoor environment, solar air heater

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Authors: Sujin Hwang, Hyerang Park, Hyunchul Kim

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The purpose of this study is to find the effectiveness of the admission simplification policy. The number of online news articles about ‘high school record’ was collected and semantically analyzed to identify and analyze the social awareness during 2014 to 2015. The main results of the study are as follows: First, there was a difference in expectations that the burden of the examinees would decrease as announced by KCUE. Thus, there was still a strain on the university entrance exam after the enforcement of the policy. Second, private tutoring is expanding in different forms, rather than reducing the policy. It is different from the prediction that examinees can prepare for university admissions without the private tutoring. Thus, the college admission rules currently enforced needs to be improved. The reasonable college admission system changes are discussed.

Keywords: education policy, private tutoring, shadow education, education admission policy

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Authors: Ikenna Charles Onyema, Prince Tolut Bako

Abstract:

A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August-December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 oC, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), Conductivity (44738.75 ± 6262.76 µS/cm), Total dissolved solids (29236.71 ± 4273.30 mg/L), Salinity (27.11 ± 3.91 ‰), Alkalinity (126.99 ± 42.81 mg/L) and Chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for Acidity (2.34 ± 0.63 mg/L), Total hardness (4711.98 ± 691.50 mg/L), Phosphate (1.1 ± 0.78 mg/L), Sulphate (2601.99 ± 447.04 mg/L) and Nitrate (0.12 ± 0.06 mg/L). Values for Total suspended solids and Biological oxygen demand values were low ( < 1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, micro-algae, lighthouse beach

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Authors: A. H. Meysami

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In this paper, the hot compression tests were carried on X45CrNiW189 valve steel (X45) in the temperature range of 1000–1200°C and the strain rate range of 0.004–0.5 s^(-1) in order to study the high temperature softening behavior of the steel. For the exact prediction of flow stress, the effective stress - effective strain curves were obtained from experiments under various conditions. On the basis of experimental results, the dynamic recrystallization fraction (DRX), AGS, hot deformation and activation energy behavior were investigated. It was found that the calculated results were in a good agreement with the experimental flow stress and microstructure of the steel for different conditions of hot deformation.

Keywords: X45CrNiW189, valve steel, hot compression test, dynamic recrystallization, hot deformation

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Authors: Tina Ternes, Florian Kleinau

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The study investigates the content and triggers of mind wandering (MW) in readers of fictional texts. It asks whether readers’ MW is productive (text-related) or unproductive (text-unrelated). Methodologically, it bridges the gap between narratological and data-driven approaches by utilizing a sentence-by-sentence self-paced reading paradigm combined with thought probes in the reading of an excerpt of A. L. Kennedy’s “Baby Blue”. Results show that the contents of MW can be linked to text properties. We validated the role of self-reference in MW and found prediction errors to be triggers of MW. Results also indicate that the content of MW often travels along the lines of the text at hand and can thus be viewed as productive and integral to interpretation.

Keywords: narratology, mind wandering, reading fiction, meta cognition

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Authors: Iftikhar Ahmad, Abulhakim Almajid

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Alumina (Al2O3) is an attractive structural ceramic however; brittleness turns Al2O3 down for advanced applications. Development of multi-phase phase ceramics systems is promising to curtail the brittleness and the incorporation of strong/elastic graphene, as third phase, into dual phase (Al2O3-SiC) is striking for mechanical upgrading purpose. Thin graphene nanosheets (GNS) were prepared by thermal exfoliation process and reinforced into dual phase ceramic system. The hybrid nanocomposite was consolidated by novel HF-IH (high-frequency induction heating) sintering furnace at 1500 °C under 50 MPa in vacuum conditions. Structural features and grain size of the resulting nanocomposite were analyzed by SEM and TEM whilst the mechanical properties were assessed by microhardness and nanoindentation techniques. The fracture toughness of the hybrid nanocomposites was appraised by direct crack measurement method. Electron microscopic investigations confirmed the preparation of thin (< 10 nm) graphene nanosheets (GNS). HF-IH sintering route condensed the three-phase (GNS-Al2O3-SiC) hybrid nanocomposite system to > 99% relative densities. SEM of the hybrid nanocomposites fractured surfaces revealed even distribution of the nanocomposite constituents and changed in fracture-mode. Structurally, 88% grain reduction into hybrid nanocomposite was also obtained. Mechanically, enhanced fracture toughness (50%) and hardness (53%) were also achieved for hybrid nanocomposites were attained against bench marked monolithic Al2O3.

Keywords: alumina, graphene, hybrid nanocomposites, rapid sintering

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Authors: Keltoum Chahour, Mickael Binois

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Due to a lack of standardization during the invasive fractional flow reserve (FFR) procedure, the index is subject to many sources of uncertainties. In this paper, we investigate -through simulation- the effect of the (FFR) device position and configuration on the obtained value of the (FFR) fraction. For this purpose, we use computational fluid dynamics (CFD) in a 3D domain corresponding to a diseased arterial portion. The (FFR) pressure captor is introduced inside it with a given length and coefficient of bending to capture the (FFR) value. To get over the computational limitations, basically, the time of the simulation is about 2h 15min for one (FFR) value; we generate a Gaussian Process (GP) model for (FFR) prediction. The (GP) model indicates good accuracy and demonstrates the effective error in the measurement created by the random configuration of the pressure captor.

Keywords: fractional flow reserve, Gaussian processes, computational fluid dynamics, drift

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Authors: Kalsoom Shaikh, Saima Memon, Riffat Sultana

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Water pollution affects amphibians because they are intimately water dependent. The permeable skin makes amphibians very sensitive to the physico-chemical parameters of their aquatic environment. They spawn in water bodies where quality of water can affect the growth, development, and survival of their eggs which may die even before hatching into larvae or developing into adults due to water contamination. Considering the importance of amphibians in agriculture, food web, ecosystem and pharmaceutics as well as adverse impact of environmental degradation on them, present study was proposed to comprehensively determine the status of their diversity and habitats in Sindh province of Pakistan so as to execute monitoring for their conservation in future. Physico-chemical parameters including pH, EC (electric conductivity), TDS (total dissolved solids), T-Hard (total hardness), T-Alk (total alkalinity), Cl (chloride), CO₂ (carbon dioxide), SO₄ (sulphate), PO₄ (phosphate), NO₂ (nitrite) and NO₃ (nitrate) were analyzed from amphibian habitats using instruments and methodology of analytical grade. The results of present study after being compared with scientific data provided by different researchers and EPA (environmental protection agency), it was concluded that amphibian habitats consisted of high values of analyzed parameters except pH and CO₂. Entire study area required an urgent implementation of conservation actions for saving amphibians.

Keywords: amphibians, diversity, habitats, physico-chemical parameters, water quality, Pakistan, Sindh Province

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Authors: Asma Perveen, M. P. Jahan

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Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: micro holes, micro EDM, Ni Alloy, discharge energy

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Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

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Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

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Authors: Mostefa Bendouba, Djebli Abdelkader, Abdelkrim Aid, Mohamed Benguediab

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The damage evolution mechanism is one of the important focuses of fatigue behaviour investigation of composite materials and also is the foundation to predict fatigue life of composite structures for engineering application. This paper is dedicated to a damage investigation under two block loading cycle fatigue conditions submitted to composite material. The loading sequence effect and the influence of the cycle ratio of the first stage on the cumulative fatigue life were studied herein. Two loading sequences, i.e., high-to-low and low-to-high cases are considered in this paper. The proposed damage indicator is connected cycle by cycle to the S-N curve and the experimental results are in agreement with model expectations. Some experimental researches are used to validate this proposition.

Keywords: fatigue, damage acumulation, composite, evolution

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Authors: Mohamed Mehdi Kadri

Abstract:

The prediction of hot shale interval in Silurian formation in a well drilled vertically in Ahnet basin Is by logging Data (Resistivity, Gamma Ray, Sonic) with the calculation of total organic carbon (TOC) using ∆ log R Method. The aim of this paper is to present Physico-chemical Properties of Hot Shale using IR spectroscopy and gas chromatography-mass spectrometry analysis; this mixture of measurements, evaluation and characterization show that the hot shale interval located in the lower of Silurian, the molecules adsorbed at the surface of shale sheet are significantly different from petroleum hydrocarbons this result are also supported with gas-liquid chromatography showed that the study extract is a hydroxypropyl.

Keywords: physic-chemical analysis, reservoirs characterization, sweet window evaluation, Silurian shale, Ahnet basin

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

Abstract:

Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Magdalena Suśniak, Joanna Karwan-Baczewska

Abstract:

Microstructure and tribological properties of AlSi5Cu2 matrix composite reinforced with SiC have been studied by microscopic examination and basic tribological properties. Composite material was produced by the mechanical alloying and spark plasma sintering (SPS) technique. The mixture of AlSi5Cu2 chips with 0, 10, 15 wt. % of SiC powder were placed in 250 ml mixing jar and milled 40 hours. To prevent the extreme cold welding the 1 wt. % of stearic acid was added to the powder mixture as a process control agent. Mechanical alloying provide to obtain composites powder with uniform distribution of SiC in matrix. Composite powders were poured into a graphite and a pulsed electric current was passed through powder under vacuum to consolidate material. Processing conditions were: sintering temperature 450°C, uniaxial pressure 32MPa, time of sintering 5 minutes. After SPS process composite samples indicate higher hardness values, lower weight loss, and lower coefficient of friction as compared with the unreinforced alloy. Light microscope micrograph of the worn surfaces and wear debris revealed that in the unreinforced alloy the prominent wear mechanism was the adhesive wear. In the AlSi5Cu2/SiC composites, by increasing of SiC the wear mechanism changed from adhesive and micro-cutting to abrasive and delamination for composite with 20 SiC wt. %. In all the AlSi5Cu2/SiC composites, abrasive wear was the main wear mechanism.

Keywords: aluminum matrix composite, mechanical alloying, spark plasma sintering, AlSi5Cu2/SiC composite

Procedia PDF Downloads 383

Authors: Vikram Munjal, Harpreet Munjal

Abstract:

A few years ago we could hardly think of Libraries' strategic plan that includes the bold and amazing prediction of a mostly digital environment for a library system. However, sheer hard work by the engineers, academicians, and librarians made it feasible. However, it requires huge expenditure and now a day‘s spending for electronic resources (e-resources) have been growing much more rapidly than have the materials budgets of which such resources are usually a part. And many libraries are spending a huge amount on e-resources. Libraries today are in the midst of a profound shift toward reliance on e-resources, and this reliance seems to have deepened in recent years as libraries have shed paper journal subscriptions to help pay for online access. This has been exercised only to cater user behavior and attitudes that seem to be changing even more quickly in this dynamic scenario.

Keywords: radio frequency identification, management, scanning, barcodes, checkout and tags

Procedia PDF Downloads 400

Authors: Suzan Abd El Majid, Menachem Bamberger, Alexander Katsman

Abstract:

Two Al-4 wt. % Cu based alloys, A201 and A201+Si were investigated in the as-cast, solution treated and aged conditions. The addition of Si was used to improve the castability of the basic alloy. The all investigated alloys in the as-cast condition contained a eutectic structure along grain boundaries (GBs) with the composition Al-50at. %Cu that was found by HRSEM EDS. Addition of Si refined the grain structure and changed the amount of the eutectic regions, their size and shape. Additionally, the A201+Si microstructure contained Si rods and small amount of Al6Mn4Cu3Fe2Si-phase. Solution treatment (ST) at 550°C for ~ 20 hours resulted in a slight dissolution of the eutectic structure in the A201 alloy while substantial dissolution and change of the eutectic composition was detected in the A201+Si alloy. After ST, the A201alloy contained θ-Al2Cu, Al5Cu2Mn3 and Al9Cu7Mn3(Fe) phases associated to the GBs, while the ST A201+Si alloy contained θ-Al2Cu, Al6Mn4Cu3(Fe,Si) and Si94Mn3Al2Cu phases. Precipitation hardening during aging at 170°C was investigated for both alloys. The microhardness of the ST A201alloy increased during aging and reached the maximum value ~ 140 HV after 2 h of aging. Initial microhardness of the ST A201+Si alloy was distinctly higher than one of the ST A201 alloy, but it decreased during the first hour of aging, then increased and reached the same maximum value ~ 140 HV after ~ 4 h of aging. It was concluded that the Si addition influenced the precipitation sequence and slowed down the age hardening process. The Si induced grain refining and evolution of the eutectic structure during the heat treatments applied are discussed.

Keywords: A201 alloys, castability, microstructure, micro-hardness

Procedia PDF Downloads 287

Authors: S. A. Agbalajobi, W. A. Bello

Abstract:

This study examines rock properties of crushed aggregate in some selected quarries in Kwara state, Nigeria. Some physical properties (chemical composition, mineral composition, particle size distribution) of gneiss sample were determined using ISRM standards. The physicomechanical properties (specific gravity, dry density, porosity, water absorption, point load index, tensile, and compressive strength) of the gneiss rock were evaluated. The analysis on the gneiss samples revealed the mean dry density and the unit weight are 2.52 g/m3, 2.63 g/m3, 2.38 g/m3; and 24.1 kN/m3, 25.78 kN/m3, 23.33 kN/m3, respectively (for locations A,B,C). The water absorption level of the gneiss rock sample ranged from 0.38 % – 0.57 % for the three locations. The mean Schmidt hammer rebound value ranged from 51.0 – 52.4 for the three locations and mean point load index values ranged from 9.89 – 10.56 MPa classified as very high strength while the uniaxial compressive strength of the rock samples revealed that its strength ranged from 120 - 139 MPa (for location A, B, and C) classified as strong rock. The aggregate impact value test and aggregate crushing value test conducted on the gneiss aggregates from the three locations in accordance with British Standard. The gneiss sample from the three locations (A, B, and C) is a good material for the production of construction works such as concrete, bricks, pavement, embankment among others, the compressive strength of the material is within the accepted limit.

Keywords: gneiss, aggregate impact, aggregate crushing, physic-mechanical properties, rock hardness

Procedia PDF Downloads 304