Search results for: hardness prediction

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Mohammad Khodaei, Mahmood Meratien, Alireza Valanezhad, Serdar Pazarlioglu, Serdar Salman, Ikuya Watanabe

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Pore size and morphology plays a crucial role on mechanical properties of porous scaffolds. In this research, titanium scaffold was prepared using space holder technique. Sodium chloride and ammonium bicarbonate were utilized as spacer agent separately. The effect of the hardness of spacer on the cell morphology was investigated using scanning electron microscopy (SEM) and optical stereo microscopy. Image analyzing software was used to interpret the microscopic images quantitatively. It was shown that sodium chloride, due to its higher hardness, maintain its morphology during cold compaction, and cause better replication in porous scaffolds.

Keywords: Spacer, Titanium Scaffold, Pore Morphology, Space Holder Technique

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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Authors: Tebogo Mabotsa, Tamba Jamiru, David Ibrahim

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Dual phase(DP) steel consists essentially of fine grained equiaxial ferrite and a dispersion of martensite. Martensite is the primary precipitate in DP steels, it is the main resistance to dislocation motion within the material. The objective of this paper is to present a relation between the intercritical annealing holding time and the hardness of a dual phase steel. The initial heat treatment involved heating the specimens to 1000oC and holding the sample at that temperature for 30 minutes. After the initial heat treatment, the samples were heated to 770oC and held for a varying amount of time at constant temperature. The samples were held at 30, 60, and 90 minutes respectively. After heating and holding the samples at the austenite-ferrite phase field, the samples were quenched in water, brine, and oil for each holding time. The experimental results proved that an equation for predicting the hardness of a dual phase steel as a function of the intercritical holding time is possible. The relation between intercritical annealing holding time and hardness of a dual phase steel heat treated at high temperatures is parabolic in nature. Theoretically, the model isdependent on the cooling rate because the model differs for each quenching medium; therefore, a universal hardness equation can be derived where the cooling rate is a variable factor.

Keywords: quenching medium, annealing temperature, dual phase steel, martensite

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Authors: J. Ptačinová, J. Ďurica, P. Jurči, M Kusý

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Ledeburitic tool steel Vanadis 6 has been subjected to sub-zero treatment (SZT) at -140 °C and -196 °C, for different durations up to 48 h. The microstructure and hardness have been examined with reference to the same material after room temperature quenching, by using the light microscopy, scanning electron microscopy, X-ray diffraction, and Vickers hardness testing method. The microstructure of the material consists of the martensitic matrix with certain amount of retained austenite, and of several types of carbides – eutectic carbides, secondary carbides, and small globular carbides. SZT reduces the retained austenite amount – this is more effective at -196 °C than at -140 °C. Alternatively, the amount of small globular carbides increases more rapidly after SZT at -140 °C than after the treatment at -140 °C. The hardness of sub-zero treated material is higher than that of conventionally treated steel when tempered at low temperature. Compressive hydrostatic stresses are developed in the retained austenite due to the application of SZT, as a result of more complete martensitic transformation. This is also why the population density of small globular carbides is substantially increased due to the SZT. In contrast, the hardness of sub-zero treated samples decreases more rapidly compared to that of conventionally treated steel, and in addition, sub-zero treated material induces a loss the secondary hardening peak.

Keywords: microstructure, Vanadis 6 tool steel, sub-zero treatment, carbides

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Authors: Jeena R. S., Sukesh Kumar A.

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Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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Authors: Julien Monnier, Isabelle Mouton, Francois Buy, Adrien Michel, Sylvain Ringeval, Joel Malaplate, Caroline Toffolon, Bernard Marini, Audrey Lechartier

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Chosen to design and assemble massive components for nuclear industry, the 316 Nb austenitic stainless steel (also called 316 Nb) suits well this function thanks to its mechanical, heat and corrosion handling properties. However, these properties might change during steel’s life due to thermal ageing causing changes within its microstructure. Our main purpose is to determine if the 316 Nb will keep its mechanical properties after an exposition to industrial temperatures (around 300 °C) during a long period of time (< 10 years). The 316 Nb is composed by different phases, which are austenite as main phase, niobium-carbides, and ferrite remaining from the ferrite to austenite transformation during the process. Our purpose is to understand thermal ageing effects on the material microstructure and properties and to submit a model predicting the evolution of 316 Nb properties as a function of temperature and time. To do so, based on Fe-Cr and 316 Nb phase diagrams, we studied the thermal ageing of 316 Nb steel alloys (1%v of ferrite) and welds (10%v of ferrite) for various temperatures (350, 400, and 450 °C) and ageing time (from 1 to 10.000 hours). Higher temperatures have been chosen to reduce thermal treatment time by exploiting a kinetic effect of temperature on 316 Nb ageing without modifying reaction mechanisms. Our results from early times of ageing show no effect on steel’s global properties linked to austenite stability, but an increase of ferrite hardness during thermal ageing has been observed. It has been shown that austenite’s crystalline structure (cfc) grants it a thermal stability, however, ferrite crystalline structure (bcc) favours iron-chromium demixion and formation of iron-rich and chromium-rich phases within ferrite. Observations of thermal ageing effects on ferrite’s microstructure were necessary to understand the changes caused by the thermal treatment. Analyses have been performed by using different techniques like Atomic Probe Tomography (APT) and Differential Scanning Calorimetry (DSC). A demixion of alloy’s elements leading to formation of iron-rich (α phase, bcc structure), chromium-rich (α’ phase, bcc structure), and nickel-rich (fcc structure) phases within the ferrite have been observed and associated to the increase of ferrite’s hardness. APT results grant information about phases’ volume fraction and composition, allowing to associate hardness measurements to the volume fractions of the different phases and to set up a way to calculate α’ and nickel-rich particles’ growth rate depending on temperature. The same methodology has been applied to DSC results, which allowed us to measure the enthalpy of α’ phase dissolution between 500 and 600_°C. To resume, we started from mechanical and macroscopic measurements and explained the results through microstructural study. The data obtained has been match to CALPHAD models’ prediction and used to improve these calculations and employ them to predict 316 Nb properties’ change during the industrial process.

Keywords: stainless steel characterization, atom probe tomography APT, vickers hardness, differential scanning calorimetry DSC, thermal ageing

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Authors: Muzeyyen Balcikanli, Selma Ozaslan, Osman Sahin, Burak Uzal, Erdogan Ozbay

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In this study, the effect of nano-CaCO3 replacement with cement on the nano-mechanical properties of cement paste was investigated. Hydrophobic and hydrophilic characteristics Two types of nano CaCO3 were replaced with Portland cement at 0, 0.5 and 1%. Water to (cement+nano-CaCO3) ratio was kept constant at 0.5 for all mixtures. 36 indentations were applied on each cement paste, and the values of nano-hardness and elastic modulus of cement pastes were determined from the indentation depth-load graphs. Then, by getting the average of them, nano-hardness and elastic modulus were identified for each mixture. Test results illustrate that replacement of hydrophilic n-CaCO3 with cement lead to a significant increase in nano-mechanical properties, however, replacement of hydrophobic n-CaCO3 with cement worsened the nano-mechanical properties considerably.

Keywords: nanoindenter, CaCO3, nano-hardness, nano-mechanical properties

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Authors: A. Nait Salah, M. Kaddami

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This work describes an investigation on the effect of filler metals diameter to weld joint, and low alloy carbon steel A516 Grade 70 is the base metal. Commercially SA516 Grade70 is frequently used for the manufacturing of pressure vessels, boilers and storage tank, etc. In fabrication industry, the hardness of the weld joint is between the important parameters to check, after heat treatment of the weld. Submerged arc welding (SAW) is used with two filler metal diameters, and this solid wire electrode is used for SAW non-alloy and for fine grain steels (SFA 5.17). The different diameters were selected (Ø = 2.4 mm and Ø = 4 mm) to weld two specimens. Both specimens were subjected to the same preparation conditions, heat treatment, macrograph, metallurgy micrograph, and micro-hardness test. Samples show almost similar structure with highest hardness. It is important to indicate that the thickness used in the base metal is 22 mm, and all specifications, preparation and controls were according to the ASME section IX. It was observed that two different filler metal diameters performed on two similar specimens demonstrated that the mechanical property (hardness) increases with decreasing diameter. It means that even the heat treatment has the same effect with the same conditions, the filler metal diameter insures a depth weld penetration and better homogenization. Hence, the SAW welding technique mentioned in the present study is favorable to implicate for the industry using the small filler metal diameter.

Keywords: ASME, base metal, micro-hardness test, submerged arc welding

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Authors: Sheng-Long Lee, Tse-An Pan

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In this study, an optical microscope (OM), electron microscope (SEM), electrical conductivity meter (% IACS), hardness test, and wear test were subjected to analyze the microstructure of the wrought Al-11Si-3Cu-0.5Mg alloys. The effect of eutectic silicon morphology and alloy hardness on wear properties was investigated. The results showed that in the cast state, the morphology of eutectic silicon modified by strontium and antimony is lamellar and finer fibrous structure. After homogenization, the eutectic Si modified by Sr coarsened, and the eutectic Si modified by Sb refined due to fragmentation. The addition of modifiers, hot rolling, and solution aging treatment can control eutectic silicon morphology and hardness. The finer eutectic silicon and higher hardness have better wear resistance. During the wearing process, a protective oxide layer, also known as Mechanical Mixed Layer (MML), is formed on the surface of the alloy. The MML has higher stability and cracking resistance in Sr-modified alloys than in Sb-modified alloys. The study found that the wearing behavior of Al-11Si-3Cu-0.5Mg alloy was enhanced by the combination of adding Sr with lower solution time and T6 peak aging.

Keywords: Al-Si-Cu-Mg alloy, eutectic silicon, heat treatment, wear property

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Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Changes in textural properties of zucchini slices under effects of frying conditions were investigated. Frying time and temperature were interested process variables like slice thickness. Slice thickness was studied at three levels (2, 3, and 4 mm). Frying process was performed at two temperature levels (160 and 180 °C) and each for five different process time periods (1, 2, 3, 5, 8 and 10 min). As frying oil sunflower oil was used. Before frying zucchini slices were thermally processes in boiling water for 90 seconds to inactivate at least 80% of plant’s enzymes. After thermal process, zucchini slices were fried in an industrial fryer at specified temperature and time pairs. Fried slices were subjected to textural profile analysis (TPA) to determine textural properties. In this extent hardness, elasticity, cohesion, chewiness, firmness values of slices were figured out. Statistical analysis indicated significant variations in the studied textural properties with process conditions (p < 0.05). Hardness and firmness were determined for fresh and thermally processes zucchini slices to compare each others. Differences in hardness and firmness of fresh, thermally processed and fried slices were found to be significant (p < 0.05). This project (113R015) has been supported by TUBITAK.

Keywords: sunflower oil, hardness, firmness, slice thickness, frying temperature, frying time

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Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

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Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: accelerometer, AdaBoost, GPS, mode prediction, support vector machine

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Authors: K. A. Mistry, I. B. Patel, A. H. Prajapati

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In the present work, the alloy of Bismuth-lead is prepared on the basis of percentage of molecular weight 9:1, 5:5 and 1:9 ratios and grown by Zone- Refining Technique under a vacuum atmosphere. The EDAX of these samples are done and the results are reported. Micro hardness test has been used as an alternative test for measuring material’s tensile properties. The effect of temperature and load on the hardness of the grown alloy has been studied. Further the comparative studies of work hardening coefficients are reported. In the present work, the alloy of Bismuth-lead is prepared on the basis of percentage of molecular weight 9:1, 5:5 and 1:9 ratios and grown by Zone- Refining Technique under a vacuum atmosphere. The EDAX of these samples are done and the results are reported. Micro hardness test has been used as an alternative test for measuring material’s tensile properties. The effect of temperature and load on the hardness of the grown alloy has been studied. Further the comparative studies of work hardening coefficients are reported.

Keywords: EDAX, hardening coefficient, micro hardness, Bi-Pb alloy

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Authors: T. Z. Butt, T. A. Tabish, K. Anjum, H. Hafeez

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A study of martensitic stainless steel surgical grade AISI 420A produced in Japan was carried out in this research work. The sample was already annealed at about 898˚C. The sample were subjected to chemical analysis, hardness, tensile and metallographic tests. These tests were performed on as received annealed and heat treated samples. In the annealed condition the sample showed 0HRC. However, on tensile testing, in annealed condition the sample showed maximum elongation. The heat treatment is carried out in vacuum furnace within temperature range 980-1035°C. The quenching of samples was carried out using liquid nitrogen. After hardening, the samples were subjected to tempering, which was carried out in vacuum tempering furnace at a temperature of 220˚C. The hardened samples were subjected to hardness and tensile testing. In hardness testing, the samples showed maximum hardness values. In tensile testing the sample showed minimum elongation. The sample in annealed state showed coarse plates of martensite structure. Therefore, the studied steels can be used as biomaterials.

Keywords: biomaterials, martensitic steel, microsrtucture, tensile testing, hardening, tempering, bioinstrumentation

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Authors: Carl van Walraven, Meltem Tuna

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Background: Network meta-analysis (NMA) quantifies the relative efficacy of 3 or more interventions from studies containing a subgroup of interventions. This study applied the analytical approach of NMA to quantify the relative accuracy of prediction models with distinct inclusion criteria that are evaluated on a common population (‘concurrent external validation’). Methods: We simulated binary events in 5000 patients using a known risk function. We biased the risk function and modified its precision by pre-specified amounts to create 15 prediction models with varying accuracy and distinct patient applicability. Prediction model accuracy was measured using the Scaled Brier Score (SBS). Overall prediction model accuracy was measured using fixed-effects methods that accounted for model applicability patterns. Prediction model accuracy was summarized as the Network Relative Model Accuracy (NeRMA) Score which ranges from -∞ through 0 (accuracy of random guessing) to 1 (accuracy of most accurate model in concurrent external validation). Results: The unbiased prediction model had the highest SBS. The NeRMA score correctly ranked all simulated prediction models by the extent of bias from the known risk function. A SAS macro and R-function was created to implement the NeRMA Score. Conclusions: The NeRMA Score makes it possible to quantify the accuracy of binomial prediction models having distinct inclusion criteria in a concurrent external validation.

Keywords: prediction model accuracy, scaled brier score, fixed effects methods, concurrent external validation

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Authors: Arvinder Kaur, Deepti Chopra

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Software Entropy Metrics for bug prediction have been validated on various software systems by different researchers. In our previous research, we have validated that Software Entropy Metrics calculated for Mozilla subsystem’s predict the future bugs reasonably well. In this study, the Software Entropy metrics are calculated for a subsystem of Android and it is noticed that these metrics are not suitable for bug prediction. The results are compared with a subsystem of Mozilla and a comparison is made between the two software systems to determine the reasons why Software Entropy metrics are not applicable for Android.

Keywords: android, bug prediction, mining software repositories, software entropy

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Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: K. Jankowski, M. Pawlikowski, A. Makuch, K. Skalski

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Depth-sensing indentation (DSI) or nanoindentation is becoming a more and more popular method of measuring mechanical properties of various materials and tissues at a micro-scale. This technique allows measurements without complicated sample preparation procedures which makes this method very useful. As a result of measurement force and displacement of the intender are obtained. It is also possible to determine three measures of hardness i.e. Martens hardness (HM), nanohardness (HIT), Vickers hardness (HV) and Young modulus EIT. In this work trabecular bone mechanical properties were investigated. The bone samples were harvested from human femoral heads during hip replacement surgery. Patients were of different age, sexes and stages of tissue degeneration caused by osteoarthritis. The specimens were divided into three groups. Each group contained samples harvested from patients of different range of age. All samples were investigated with the same measurement conditions. The maximum load was Pmax=500 mN and the loading rate was 500 mN/min. The tests were held without hold at the peak force. The tests were conducted with indenter Vickers tip and spherical tip of the diameter 0.2 mm. Each trabecular bone sample was tested 7 times in a close area of the same trabecula. The measured loading P as a function of indentation depth allowed to obtain hysteresis loop and HM, HIT, HV, EIT. Results for arbitrarily chosen sample are HM=289.95 ± 42.31 MPa, HIT=430.75 ± 45.37 MPa, HV=40.66 ± 4.28 Vickers, EIT=7.37 ± 1.84 GPa for Vickers tip and HM=115.19 ± 15.03 MPa, HIT=165.80 ± 19.30 MPa, HV=16.90 ± 1.97 Vickers, EIT=5.30 ± 1.31 GPa for spherical tip. Results of nanoindentation tests show that this method is very useful and is perfect for obtaining mechanical properties of trabecular bone. Estimated values of elastic modulus are similar. The differences between hardness are significant but it is a result of using two different types of tips. However, it has to be emphasised that the differences in the values of elastic modulus and hardness result from different testing protocols, anisotropy and asymmetry of the micro-samples and the hydration of bone.

Keywords: human bone, mechanical properties, nano hardness nanoindentation, trabecular bone

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Authors: Chang Su Woo, Hyun Sung Park

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Useful lifetime evaluation of chevron rubber spring was very important in design procedure to assure the safety and reliability. It is, therefore, necessary to establish a suitable criterion for the replacement period of chevron rubber spring. In this study, we performed characteristic analysis and useful lifetime prediction of chevron rubber spring. Rubber material coefficient was obtained by curve fittings of uni-axial tension, equi bi-axial tension and pure shear test. Computer simulation was executed to predict and evaluate the load capacity and stiffness for chevron rubber spring. In order to useful lifetime prediction of rubber material, we carried out the compression set with heat aging test in an oven at the temperature ranging from 50°C to 100°C during a period 180 days. By using the Arrhenius plot, several useful lifetime prediction equations for rubber material was proposed.

Keywords: chevron rubber spring, material coefficient, finite element analysis, useful lifetime prediction

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Rohollah Ghasemi, Arvin Ghorbani

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This study investigates the effect of austempering temperature on microstructure and scratch behavior of the austempered heat-treated compacted graphite irons. The as-cast was used as base material for heat treatment practices. The samples were extracted from as-cast ferritic CGI pieces and were heat treated under austenitising temperature of 900°C for 60 minutes which followed by quenching in salt-bath at different austempering temperatures of 275°C, 325°C and 375°C. For all heat treatments, an austempering holding time of 30 minutes was selected for this study. Light optical microscope (LOM) and scanning electron microscope (SEM) and electron back scattered diffraction (EBSD) analysis confirmed the ausferritic matrix formed in all heat-treated samples. Microscratches were performed under the load of 200, 600 and 1000 mN using a sphero-conical diamond indenter with a tip radius of 50 μm and induced cone angle 90° at a speed of 10 μm/s at room temperature ~25°C. An instrumented nanoindentation machine was used for performing nanoindentation hardness measurement and microscratch testing. Hardness measurements and scratch resistance showed a significant increase in Brinell, Vickers, and nanoindentation hardness values as well as microscratch resistance of the heat-treated samples compared to the as-cast ferritic sample. The increase in hardness and improvement in microscratch resistance are associated with the formation of the ausferrite matrix consisted of carbon-saturated retained austenite and acicular ferrite in austempered matrix. The maximum hardness was observed for samples austempered at 275°C which resulted in the formation of very fine acicular ferrite. In addition, nanohardness values showed a quite significant variation in the matrix due to the presence of acicular ferrite and carbon-saturated retained austenite. It was also observed that the increase of austempering temperature resulted in increase of volume of the carbon-saturated retained austenite and decrease of hardness values.

Keywords: austempered CGI, austempering, scratch testing, scratch plastic deformation, scratch hardness

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Authors: Qiang Zhang, Chun Yuan

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Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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Authors: J. K. Alhassan, C. S. Actsu

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This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: Xingguo Feng, Hui Zhou, Kaifeng Zhang, Zhao Jiang, Hanjun Hu, Jun Zheng, Hong Hao

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TiN and TiC films have been prepared on Ti6Al4V alloy substrates by plasma-based ion implantation. The effect of N+C and Ti+N hybrid ion implantation at 50 kV, and Ti+C hybrid ion implantation at 20 kV, 35 kV and 50 kV extraction voltages on mechanical properties at a dose of 2×10¹⁷ ions / cm² was studied. The chemical states and microstructures of the implanted samples were investigated using X-ray photoelectron (XPS), and X-ray diffraction (XRD), together with the mechanical and tribological properties of the samples were characterized using nano-indentation and ball-on-disk tribometer. It was found that the modified layer by Ti+C implanted at 50 kV was composed of mainly TiC and Ti-O bond and the layer of Ti+N implanted at 50 kV was observed to be TiN and Ti-O bond. Hardness tests have shown that the hardness values for N+C, Ti+N, and Ti+C hybrid ion implantation samples were much higher than the un-implanted ones. The results of wear tests showed that both Ti+C and Ti+N ion implanted samples had much better wear resistance compared un-implanted sample. The wear rate of Ti+C implanted at 50 kV sample was 6.7×10⁻⁵mm³ / N.m, which was decreased over one order than unimplanted samples.

Keywords: plasma ion implantation, x-ray photoelectron (XPS), hardness, wear

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Esther T. Akinlabi, Stephen A. Akinlabi

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This paper reports on the effects of heat treatment on 3CR12 and AISI 316 stainless steel grades. Heat treatment was conducted on the steel grades and cooled using two different media; air and water in order to study the effect of each medium on the evolving properties of the samples. The heat treated samples were characterized through the evolving microstructure and hardness. It was found that there was a significant grain size reduction in both the heat treated stainless steel specimens compared to the parent materials. The finer grain sizes were achieved as a result of impediment to growth of one phase by the other. The Vickers micro-hardness values of the heat treated samples were higher compared to the parent materials due to the fact that each of the steel grades had a proportion of martensitic structures in their microstructures.

Keywords: austenite, ferrite, grain size, hardness, martensite, microstructure and stainless steel

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Authors: Raffaella Sesana, Nazanin Sheibanian, Luca Corsaro, Sedat Özbilen, Rocco Lupoi, Francesco Artusio

Abstract:

High Entropy Alloy (HEA) coatings of Al0.1-0.5CoCrCuFeNi and MnCoCrCuFeNi on Mg substrates were prepared from mechanically alloyed HEA powder feedstocks and at three different Cold Spray (CS) process gas (N2) temperatures (650, 750 and 850°C). Mechanically alloyed and cold-sprayed HEA coatings were characterized by macro photography, OM, SEM+EDS study, micro-hardness testing, roughness, and porosity measurements. As a result of mechanical alloying (MA), harder particles are deformed and fractured. The particles in the Cu-rich region were coarser and more globular than those in the A1 phase, which is relatively soft and ductile. In addition to the A1 particles, there were some separate Cu-rich regions. Due to the brittle nature of the powder and the acicular shape, Mn-HEA powder exhibited a different trend with smaller particle sizes. It is observed that MA results in a loose structure characterized by many gaps, cracks, signs of plastic deformation, and small particles attached to the surface of the particle. Considering the experimental results obtained, it is not possible to conclude that the chemical composition of the high entropy alloy influences the roughness of the coating. It has been observed that the deposited volume increases with temperature only in the case of Al0.1 and Mg-based HEA, while for the rest of the Al-based HEA, there are no noticeable changes. There is a direct correlation between micro-hardness and the chemical composition of a coating: the micro-hardness of a coating increases as the percentage of aluminum increases in the sample. Compared to the substrate, the coating has a much higher hardness, and the hardness measured at the interface is intermediate.

Keywords: characterisation, cold spraying, HEA coatings, SEM+EDS

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Authors: Jiun Jeon, Byung-Ju Yi

Abstract:

This paper investigates modeling and shape prediction of elastic kinematic chains such as colonoscopy. 2D and 3D models of elastic kinematic chains are suggested and their behaviors are demonstrated through simulation. To corroborate the effectiveness of those models, experimental work is performed using a magnetic sensor system.

Keywords: elastic kinematic chain, shape prediction, colonoscopy, modeling

Procedia PDF Downloads 565

Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

Procedia PDF Downloads 161