Search results for: corrosion prediction ductile fracture

Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Liang Zhao, Guangwen Wang, Guichang Liu

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Constant potometer is an important component of pipeline anti-corrosion systems in the chemical industry. Based on Internet of Things (IoT) technology, Programmable Logic Controller (PLC) technology and database technology, this paper developed a set of a constant potometer remote monitoring management system. The remote monitoring and remote adjustment of the working status of the constant potometer are realized. The system has real-time data display, historical data query, alarm push management, user permission management, and supporting Web access and mobile client application (APP) access. The actual engineering project test results show the stability of the system, which can be widely used in cathodic protection systems.

Keywords: internet of things, pipe corrosion protection, potentiostat, remote monitoring

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Authors: I. Slim, H. Akkari, A. Ben Abdallah, I. Bhouri, M. Hedi Bedoui

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Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.

Keywords: fractal, micro-architecture analysis, multifractal, osteoporosis, SVM

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Danladi Ali, Abdullahi Mukaila

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In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction.

Keywords: decomposition, clustering, propagation, model, wavelet, signal strength and spectral efficiency

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Etienne Alain Feukeu, L. W. Snyman

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Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

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Authors: Aboozar Aghaei, Kamran Dehghani

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In the present work, the dissimilar Monel400 and SS316 were joined by friction stir welding (FSW). The applied rotating speed was 400 rpm, whereas the traverse speed varied between 50 and 150 mm/min. At a constant rotating speed, the sound welds were obtained at the welding speeds of 50 and 100 mm/min. However, a groove-like defect was formed when the welding speed exceeded 100 mm/min. The mechanical properties of the joints were evaluated using tensile and fatigue tests. The fatigue strength of dissimilar FSWed specimens was higher than that of both Monel400 and SS316. To study the failure behavior of FSWed specimens, the fracture surfaces were analyzed using a scanning electron microscope (SEM). The failure analysis indicates that different mechanisms may contribute to the fracture of welds. This was attributed to the dissimilar characteristics of dissimilar materials exhibiting different failure behaviors.

Keywords: frictions stir welding, stainless steel, Monel400, mechanical properties

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Authors: M. J. Kim, D. B. Lee

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Centrifugal casting is a metal casting method that uses forces make by centripetal acceleration to distribute molten material in mold. Centrifugal cast parts manufactured in industry contain gas pipes and water supply lines, moreover rings, turbocharger, bushings, brake drums. Turbochargers were exposed to exhaust temperatures of 900-1050°C require a material for the corrosion resistance that will withstand such high component temperatures during the entire service life of the vehicle. Hence, the study of corrosion resistance for turbocharger is important for practical application. DIN1.4091 steels were used widely. The DIN1.4091 steels whose compositions were Fe-34.4Cr-14.5Ni-2.5Mo-0.4W-0.4Mn-0.5Si-(0.009 or 0.35)S (wt.%) were centrifugally cast, and oxidized at 900°C for 50-200 h in order to find the effect of sulfur on the high-temperature oxidation of Fe-34.4Cr-14.5Ni-2.5Mo-0.4W-0.4Mn-0.5Si-(0.009 or 0.35)S (wt.%) alloys. These alloys formed oxide scales that consisted primarily of Cr₂O₃ as the major oxide and Cr₂MnO₄ as the minor one through preferential oxidation of Cr and Mn. Cr formed a thin CrOx oxide film on the surface to prevent further oxidation, and when it is added more than 20%, the sulphide decreased corrosion rate. The high affinity of Mn with S, led to the formation of scattered MnS inclusions, particularly in the 0.35S-containing cast alloy. Sulfur was harmful to the oxidation resistance because it deteriorated the scale/alloy adherence so as to accelerate the adherence and compactness of the formed scales. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1A2B1013169).

Keywords: centrifugal casting, turbocharger, sulfur, oxidation, Fe-34.4Cr-14.5Ni alloy

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: A. Mohamed, A. El-Aziz

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The pH of the body plays a great role in the degradation kinetics of biodegradable Mg-Ca orthopedic implants. At the location of fracture, the pH of the body becomes no longer neutral which draws the attention towards studying a range of different pH values of the body fluid. In this study, the pH of Hank’s balanced salt solution (HBSS) was modified by phosphate buffers into an aggressive acidic pH 1.8, a slightly acidic pH 5.3 and an alkaline pH 8.1. The biodegradation of Mg-0.8Ca implant was tested in those three different media using immersion test and electrochemical polarization means. It was proposed that the degradation rate has increased with decreasing the pH of HBSS. The immersion test revealed weight gain for all the samples followed by weight loss as the immersion time increased. The highest weight gain was pronounced for the acidic pH 1.8 and the least weight gain was observed for the alkaline pH 8.1. This was in agreement with the electrochemical polarization test results where the degradation rate was found to be high (7.29 ± 2.2 mm/year) in the aggressive acidic solution of pH 1.8 and relatively minimum (0.31 ± 0.06 mm/year) in the alkaline medium of pH 8.1. Furthermore, it was confirmed that the pH of HBSS has reached a steady state of an alkaline pH (~pH 11) at the end of the two-month immersion period regardless of the initial pH of the solution. Finally, the corrosion products formed on the samples’ surface were investigated by SEM, EDX and XRD analyses that revealed the formation of magnesium and calcium phosphates with different morphologies according to the pH.

Keywords: biodegradable, electrochemical polarization means, orthopedics, immersion test, simulated body fluid

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Authors: Mohamad Saeed Ahrari-Khafi, Abutorab Tabatabai-Naini, Niloofar Ajvadi

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Scapular fracture is not common in horses, due to the proper protection of scapular muscles. However, if it happens, it can cause lameness in horses. Because of the overlapping of the scapula on the contralateral scapula and the thorax, usually radiography cannot be helpful in evaluation, except in small amount of its ventral part. Although ultrasonography is mainly used for diagnosis of soft tissue injuries, it also can be used for evaluation of bone surface abnormalities. This study was intended to document the normal ultrasonographic appearance of the equine scapula. Right forelimb of six horses was used. To facilitate the image assessment, a zoning system was developed. Ultrasonography was performed by using a 5-11 MHz linear array transducer. Ultrasonographic anatomy of scapula in different parts and planes was imaged and documented, hoping to help practitioners to diagnose fractures and injuries. Results showed that ultrasonography is capable to depict different parts of the scapula and regional muscles, and can be used for detecting fractures and other abnormalities.

Keywords: horse, scapula, scapular fracture, ultrasonography

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Authors: Francis Mark A. Fernandez, Chelca Ubay, Armithan Suguitan

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Regions or provinces in a definite state certainly contribute to the economy of their mainland. These regions or provinces are the ones supplying the mainland with different resources and assets. Thus, with a certain region separating from the mainland would indeed impinge the heart of an entire state to develop and expand. With these, the researchers decided to study on the effects of the separation of one’s region to its mainland and the consequences that will take place if the mainland would rule out the region to separate from them. The researchers wrote this paper to present the causes of the separation of Catalonia from Spain and the prediction regarding the pursuance of this region to revolt from its mainland, Spain. In conducting this research, the researchers utilized two analyses, namely: qualitative and quantitative. In qualitative, numerous of information regarding the existing experiences of the citizens of Catalonia were gathered by the authors to give certainty to the prediction of the researchers. Besides this undertaking, the researchers will also gather needed information and figures through books, journals and the published news and reports. In addition, to further support this prediction under qualitative analysis, the researchers intended to operate the Phenomenological research in which the examiners will exemplify the lived experiences of each citizen in Catalonia. Moreover, the researchers will utilize one of the types of Phenomenological research which is hermeneutical phenomenology by Van Manen. In quantitative analysis, the researchers utilized the regression analysis in which it will ascertain the causality in an underlying theory in understanding the relationship of the variables. The researchers assigned and identified different variables, wherein the dependent variable or the y which represents the prediction of the researchers, the independent variable however or the x represents the arising problems that grounds the partition of the region, the summation of the independent variable or the ∑x represents the sum of the problem and finally the summation of the dependent variable or the ∑y is the result of the prediction. With these variables, using the regression analysis, the researchers will be able to show the connections and how a single variable could affect the other variables. From these approaches, the prediction of the researchers will be specified. This research could help different states dealing with this kind of problem. It will further help certain states undergoing this problem by analyzing the causes of these insurgencies and the effects on it if it will obstruct its region to consign their full-pledge autonomy.

Keywords: autonomy, liberty, prediction, separation

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Authors: Anuoluwapo S. Taiwo, David S. Ayre, Morteza Khorami, Sameer S. Rahatekar

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This investigation aims to characterize the effect of Corn Cob (CC), an agricultural waste, for potential use as a filler material, reducing cement in natural fibre-reinforced cement composite boards used for building applications in low-cost housing estates in developing countries. The corn cob is readily and abundantly available in many West African States. However, this agricultural waste product has not been put to any effective use. Hence, the objective of the current research is to convert this massive agro-waste resource into a potential material for use as filler materials reducing cement contents in fibre-cement board production. Kraft pulp fibre-reinforced cement composite boards were developed with the incorporation of the corn cob powder at varying percentages of 1 – 4% as filler materials to reduce the cement content, using a laboratory-simulated vacuum de-watering process. The mechanical properties of the developed cement boards were characterized through a three-point bending test, while the fractured morphology of the cement boards was examined through a Scanning Electron Microscope (SEM). Results revealed that the flexural strength of the composite board improved significantly with an optimum enhancement of 39% when compared to the reference sample without corn cob replacement, however, the flexural behaviour (ductility) of the composite board was slightly affected by the addition of the corn cob powder at higher percentage. SEM observation of the fractured surfaces revealed good bonding at the fibre-matrix interface as well as a ductile-to-brittle fracture mechanism. Overall, the composite board incorporated with 2% corn cob powder as filler materials had the optimum properties which satisfied the minimum requirements of relevant standards for fibre cement flat sheets.

Keywords: agricultural waste, building applications, fibre-cement board, kraft pulp fibre, sustainability

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Authors: M. Esmailian, M. Shakouri, A. Mottahedi, S. G. Shabestari

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Heat treatable aluminium alloys such as 7075 and 7055, because of high strength and low density, are used widely in aircraft industry. For best mechanical properties, T6 heat treatment has recommended for this regards, but this temper treatment is sensitive to corrosion induced and Stress Corrosion Cracking (SCC) damage. For improving this property, the over-aging treatment (T7) applies to this alloy, but it decreases the mechanical properties up to 30 percent. Hence, to increase the mechanical properties, without any remarkable decrease in SCC resistant, Retrogression and Re-Aging (RRA) heat treatment is used. This treatment performs in a relatively short time. In this paper, the RRA heat treatment was applied to 7055 aluminum alloy and then effect of RRA time on the mechanical properties of 7055 has been investigated. The results show that the 40 minute time is suitable time for retrogression of 7055 aluminum alloy and ultimate strength increases up to 625MPa.

Keywords: 7055 Aluminum alloy, mechanical properties, SCC resistance, heat Treatment

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Authors: S. K. Ghosh, C. Srivastava, P. K. Limaye, V. Kain

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Electroplated hard chromium is widely known in coatings and surface finishing, automobile and aerospace industries because of its excellent hardness, wear resistance and corrosion properties. However, its precursor, Cr+6 is highly carcinogenic in nature and a consensus has been adopted internationally to eradicate this coating technology with an alternative one. The search for alternate coatings to electroplated hard chrome is continuing worldwide. Various alloys and nanocomposites like Co-W alloys, Ni-Graphene, Ni-diamond nanocomposites etc. have already shown promising results in this regard. Basically, in this study, electroless Ni-P alloys with excellent corrosion resistance was taken as the base matrix and incorporation of tungsten as third alloying element was considered to improve the hardness and wear resistance of the resultant alloy coating. The present work is focused on the preparation of Ni–W–P coatings by electrodeposition with different content of phosphorous and its effect on the electrochemical, mechanical and tribological performances. The results were also compared with Ni-W alloys. Composition analysis by EDS showed deposition of Ni-32.85 wt% W-3.84 wt% P (designated as Ni-W-LP) and Ni-18.55 wt% W-8.73 wt% P (designated as Ni-W-HP) alloy coatings from electrolytes containing of 0.006 and 0.01M sodium hypophosphite respectively. Inhibition of tungsten deposition in the presence of phosphorous was noted. SEM investigation showed cauliflower like growth along with few microcracks. The as-deposited Ni-W-P alloy coating was amorphous in nature as confirmed by XRD investigation and step-wise crystallization was noticed upon annealing at higher temperatures. For all the coatings, the nanohardness was found to increase after heat-treatment and typical nanonahardness values obtained for 400°C annealed samples were 18.65±0.20 GPa, 20.03±0.25 GPa, and 19.17±0.25 for alloy coatings Ni-W, Ni-W-LP and Ni-W-HP respectively. Therefore, the nanohardness data show very promising results. Wear and coefficient of friction data were recorded by applying a different normal load in reciprocating motion using a ball on plate geometry. Post experiment, the wear mechanism was established by detail investigation of wear-scar morphology. Potentiodynamic measurements showed coating with a high content of phosphorous was most corrosion resistant in 3.5wt% NaCl solution.

Keywords: corrosion, electrodeposition, nanohardness, Ni-W-P alloy coating

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Authors: Rejane Maria P. da Silva, Mariana X. Milagre, João Victor de S. Araujo, Leandro A. de Oliveira, Renato A. Antunes, Isolda Costa

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The Al-Cu-Li alloys are advanced materials for aerospace application because of their interesting mechanical properties and low density when compared with conventional Al-alloys. However, Al-Cu-Li alloys are susceptible to localized corrosion. The near-surface deformed layer (NSDL) induced by the rolling process during the production of the alloy and its removal by polishing can influence on the corrosion susceptibility of these alloys. In this work, the influence of surface preparation effects on the electrochemical activity of AA2098-T351 (Al–Cu–Li alloy) was investigated using a correlation between surface chemistry, microstructure, and electrochemical activity. Two conditions were investigated, polished and as-received surfaces of the alloy. The morphology of the two types of surfaces was investigated using confocal laser scanning microscopy (CLSM) and optical microscopy. The surface chemistry was analyzed by X-ray Photoelectron Spectroscopy (XPS) and energy dispersive X-ray spectroscopy (EDS). Global electrochemical techniques (potentiodynamic polarization and EIS technique) and a local electrochemical technique (Localized Electrochemical Impedance Spectroscopy-LEIS) were used to examine the electrochemical activity of the surfaces. The results obtained in this study showed that in the as-received surface, the near-surface deformed layer (NSDL), which is composed of Mg-rich bands, influenced the electrochemical behavior of the alloy. The results showed higher electrochemical activity to the polished surface condition compared to the as-received one.

Keywords: Al-Cu-Li alloys, surface preparation effects, electrochemical techniques, localized corrosion

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

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MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Mahdi Babaee, Arnaud Castel

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One of the main hurdles for commercial adaptation of geopolymer concrete (GPC) as a low-embodied-carbon alternative for Portland cement concrete (PCC) is the durability aspects and its long-term performance in aggressive/corrosive environments. GPC is comparatively a new engineering material and in the absence of a track record of successful durability performance, proper experimental studies to investigate different durability-related characteristics of GPC seem inevitable. In this context, this paper aims to study the bulk electrical resistivity of geopolymer mortars fabricated of blends of low-calcium fly ash (FA) and ground granulated blast-furnace slag (GGBS). Bulk electrical resistivity is recognized as one of the most important parameters influencing the rate of corrosion of reinforcing bars during the propagation phase of corrosion. To investigate the effect of alkali concentration on the resistivity of the samples, 100x200 mm mortar cylinders were cast at different alkali concentration levels, whereas the modulus ratio (the molar ratio of SiO2/Na2O) was fixed for the mixes, and the bulk electrical resistivity was then measured. Also, the effect of the binder composition was assessed with respect to the ratio of FA to GGBS used. Results show a superior performance of samples with higher GGBS content. Lower concentration of the solution has increased the resistivity by reducing the amount of mobile alkali ions in the pore solution. Moreover, GGBS-based samples showed a much sharper increase in the electrical resistivity with decreasing the moisture content.

Keywords: bulk resistivity, corrosion, durability, geopolymer concrete

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Authors: Yenni Kurniawati

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Students Prediction Skill in chemistry experiments is an important skill for pre-service chemistry students to stimulate students reflective thinking at each stage of many chemistry experiments, qualitatively and quantitatively. A Virtual Chemistry Laboratory was designed to give students opportunities and times to practicing many kinds of chemistry experiments repeatedly, everywhere and anytime, before they do a real experiment. The Virtual Chemistry Laboratory content was constructed using the Model of Educational Reconstruction and developed to enhance students ability to predicted the experiment results and analyzed the cause of error, calculating the accuracy and precision with carefully in using chemicals. This research showed students changing in making a decision and extremely beware with accuracy, but still had a low concern in precision. It enhancing students level of reflective thinking skill related to their prediction skill 1 until 2 stage in average. Most of them could predict the characteristics of the product in experiment, and even the result will going to be an error. In addition, they take experiments more seriously and curiously about the experiment results. This study recommends for a different subject matter to provide more opportunities for students to learn about other kinds of chemistry experiments design.

Keywords: virtual chemistry laboratory, chemistry experiments, prediction skill, pre-lab experiences

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Authors: Adamantini Loukodimou, David Weston, Shiladitya Paul

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Offshore structures are subjected to harsh environments. It is documented that carbon steel needs protection from corrosion. The combined effect of UV radiation, seawater splash, and fluctuating temperatures diminish the integrity of these structures. In addition, the possibility of damage caused by floating ice, seaborne debris, and maintenance boats make them even more vulnerable. Their inspection and maintenance when far out in the sea are difficult, risky, and expensive. The most known method of mitigating corrosion of offshore structures is the use of cathodic protection. There are several zones in an offshore wind turbine. In the atmospheric zone, due to the lack of a continuous electrolyte (seawater) layer between the structure and the anode at all times, this method proves inefficient. Thus, the use of protective coatings becomes indispensable. This research focuses on the atmospheric zone. The conversion of commercially available and conventional paint (epoxy) system to an autonomous self-healing paint system via the addition of suitable encapsulated healing agents and catalyst is investigated in this work. These coating systems, which can self-heal when damaged, can provide a cost-effective engineering solution to corrosion and related problems. When the damage of the paint coating occurs, the microcapsules are designed to rupture and release the self-healing liquid (monomer), which then will react in the presence of the catalyst and solidify (polymerization), resulting in healing. The catalyst should be compatible with the system because otherwise, the self-healing process will not occur. The carbon steel substrate will be exposed to a corrosive environment, so the use of a sacrificial layer of Zn is also investigated. More specifically, the first layer of this new coating system will be TSZA (Thermally Sprayed Zn85/Al15) and will be applied on carbon steel samples with dimensions 100 x 150 mm after being blasted with alumina (size F24) as part of the surface preparation. Based on the literature, it corrodes readily, so one additional paint layer enriched with microcapsules will be added. Also, the reaction and the curing time are of high importance in order for this bilayer system of coating to work successfully. For the first experiments, polystyrene microcapsules loaded with 3-octanoyltio-1-propyltriethoxysilane were conducted. Electrochemical experiments such as Electrochemical Impedance Spectroscopy (EIS) confirmed the corrosion inhibiting properties of the silane. The diameter of the microcapsules was about 150-200 microns. Further experiments were conducted with different reagents and methods in order to obtain diameters of about 50 microns, and their self-healing properties were tested in synthetic seawater using electrochemical techniques. The use of combined paint/electrodeposited coatings allows for further novel development of composite coating systems. The potential for the application of these coatings in offshore structures will be discussed.

Keywords: corrosion mitigation, microcapsules, offshore wind turbines, self-healing

Procedia PDF Downloads 114

Authors: Tuji Mohammed Sani

Abstract:

Back ground: An open tibial fracture is an injury where the fractured bone directly communicates with the outside environment. Due to the specific anatomical features of the tibia (limited soft tissue coverage), more than quarter of its fractures are classified as open, representing the most common open long-bone injuries. Open tibial fractures frequently cause significant bone comminution, periosteal stripping, soft tissue loss, contamination and are prone to bacterial entry with biofilm formation, which increases the risk of deep bone infection. Objective: The main objective of the study was to determine Prevalence of infection and its associated factors in surgically treated open tibial fracture in Addis Ababa Burn Emergency and Trauma (AaBET) center. Method: A facility based retrospective cross-sectional study was conducted among patient treated for open tibial fracture at AaBET center from September 2018 to September 2021. The data was collected from patient’s chart using structured data collection form, and Data was entered and analyzed using SPSS version 26. Bivariable and multiple binary logistic regression were fitted. Multicollinearity was checked among candidate variables using variance inflation factor and tolerance, which were less than 5 and greater than 0.2, respectively. Model adequacy were tested using Hosmer-Lemeshow goodness of fitness test (P=0.711). AOR at 95% CI was reported, and P-value < 0.05 was considered statistically significant. Result: This study found that 33.9% of the study participants had an infection. Initial IV antibiotic time (AOR=2.924, 95% CI:1.160- 7.370) and time of wound closure from injury (AOR=3.524, 95% CI: 1.798-6.908), injury to admission time (AOR=2.895, 95% CI: 1.402 – 5.977). and definitive fixation method (AOR=0.244, 95% CI: 0.113 – 0.4508) were the factors found to have a statistically significant association with the occurrence of infection. Conclusion: The rate of infection in open tibial fractures indicates that there is a need to improve the management of open tibial fracture treated at AaBET center. Time from injury to admission, time from injury to first debridement, wound closure time, and initial Intra Venous antibiotic time from the injury are an important factor that can be readily amended to improve the infection rate. Whether wound closed before seven days or not were more important factor associated with occurrences of infection.

Keywords: infection, open tibia, fracture, magnitude

Procedia PDF Downloads 82

Authors: M. Benzerara, B. Redjel, B. Kebaili

Abstract:

The cracking of the concrete is a more crucial problem with the development of the complex structures related to technological progress. The projections in the knowledge of the breaking process make it possible today for better prevention of the risk of the fracture. The breaking strength brutal of a quasi-fragile material like the concrete called Toughness is measured by a breaking value of the factor of the intensity of the constraints K1C for which the crack is propagated, it is an intrinsic property of the material. Many studies reported in the literature treating of the concrete were carried out on specimens which are in fact inadequate compared to the intrinsic characteristic to identify. We started from this established fact, in order to compare the evolution of the parameter of toughness K1C measured by calling upon ordinary concrete specimens of three prismatic geometries different (10*10*40) Cm3, (12*12*60) Cm3 & (5*20*120) Cm3 containing from the side notches various depths simulating of the cracks was set up.The notches are carried out using triangular pyramidal plates into manufactured out of sheet coated placed at the center of the specimens at the time of the casting, then withdrawn to leave the trace of a crack. The tests are carried out in 3 points bending test in mode 1 of fracture, by using the techniques of mechanical fracture. The evolution of the parameter of toughness K1C measured with the three geometries specimens gives almost the same results. They are acceptable and return in the beach of the results determined by various researchers (toughness of the ordinary concrete turns to the turn of the 1 MPa √m). These results inform us about the presence of an economy on the level of the geometry specimen (5*20*120) Cm3, therefore, to use plates specimens later if one wants to master the toughness of this material complexes, astonishing but always essential that is the concrete.

Keywords: concrete, fissure, specimen, toughness

Procedia PDF Downloads 298

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

Procedia PDF Downloads 138

Authors: Omar Alhamad, Waleed Eid

Abstract:

Reinforced concrete is a concrete lined with steel so that the materials work together in the resistance forces. Reinforcement rods or mesh are used for tensile, shear, and sometimes intense pressure in a concrete structure. Reinforced concrete is subject to many natural problems or industrial errors. The result of these problems is that it reduces the efficiency of the reinforced concrete or its usefulness. Some of these problems are cracks, earthquakes, high temperatures or fires, as well as corrosion of reinforced iron inside reinforced concrete. There are also factors of ancient buildings or monuments that require some techniques to preserve them. This research presents some general information about reinforced concrete, the pros and cons of reinforced concrete, and then presents a series of literary studies of some of the late published researches on the subject of reinforced concrete and how to preserve it, propose solutions or treatments for the treatment of reinforced concrete problems, raise efficiency and quality for a longer period. These studies have provided advanced and modern methods and techniques in the field of reinforced concrete.

Keywords: reinforced concrete, treatment, concrete, corrosion, seismic, cracks

Procedia PDF Downloads 152

Authors: S. Zouari, H. Ghorbel, H. Liao, R. Elleuch

Abstract:

Research is increasingly moving towards the use of surface treatment processes to limit environmental effects. Electrolytic plating has traditionally been seen as a way to protect brass products, especially faucets, from mechanical and chemical damage. However, this method was not effective industrially, economically and ecologically. The aim of this work is to develop non-usual polymer coatings for brass faucets in order to improve the performance of brass and to replace electrolytic chromium coatings, thereby reducing environmental impact. Fluorinated-Ethylene-Propylene polymer (FEP) was chosen for its excellent mechanical and chemical properties and its good environmental performance. This coating was developed by spraying (painting) process onto brass substrates. The coatings obtained were characterized using a scanning electron microscope to evaluate the morphology of the deposits and their porosity rate. Grid adhesion, surface energy and corrosion tests (salt spray) were also performed to evaluate the mechanical and chemical behavior of these coatings properly. The results show that the deposits obtained have a homogeneous microstructure with a very low porosity rate. The results of the grid adhesion test prove the conformity of the test according to the NF077 standard. The coatings have a hydrophobic character following the low values of surface energy obtained and a very good resistance to corrosion. These results are interesting and may represent real technological issues in the industrial field.

Keywords: FEP coatings, spraying process, brass, adhesion, surface energy, corrosion resistance

Procedia PDF Downloads 141