Search results for: random composites

Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

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Authors: F. Z. Benabid, S. Kridi, F. Zouai, D. Benachour

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The aim of present work is to characterize the PP/TiO2 blends as composites, and study the effect of TiO2 on properties of different compositions and the evaluation of the effectiveness of the method used for filler treatment. Nanocomposite samples were synthesized by molten route in an internal mixer. The TiO2 nanoparticles were treated with stearic acid in order to obtain a good dispersion, and the demonstration of the effectiveness of the treatment on the morphology and roughness of the nanofiller was established by microstructural analysis by FTIR and AFM. The various developed nanocomposite compositions were characterized by different methods; i.e. FTIR, XRD, SEM and optical microscopy. Rheological, dielectric and mechanical studies were also performed. The results showed a remarkable increase in the impact strength results which increased about 39% compared to neat PP. The rheological study showed an increase in the fluidity in all developed composite compositions, involved by the good dispersion of TiO2 particles.

Keywords: composites, PP, TiO2, comixing, mechanical treatment

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Authors: M. A. Moussa, M. H. Abdel Rehim, G.M. Turky

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Polyaniline composites with carbon nitride, to overcome compatibility restriction with graphene, were prepared with the solution method. FTIR and Uv-vis spectra were used for structural conformation. While XRD and XPS confirmed the structures in addition to estimation of nitrogen atom surroundings, the pore sizes and the active surface area were determined from BET adsorption isotherm. The electrical and dielectric parameters were measured and calculated with BDS .

Keywords: carbon nitride, dynamic relaxation, electrical conductivity, polyaniline

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Jain Jyoti, Jain Shorab, Sinha Shishir

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In the field of material engineering, composites are in great concern for their nonbiodegradability and their cost. In order to reduce its cost and weight, plant derived fibers witnessed miraculous triumph. Plant fibers can be of different types like seed fibers, blast fibers, leaf fibers, etc. Composites can be reinforced with exclusively one type of natural fiber or also can be combined with two or more different types of natural or synthetic fibers to boost up their specific properties. Among all natural fibers, wheat straw, bagasse, kenaf, pineapple leaf, banana, coir, ramie, flax, etc. pineapple leaf fibers have very good mechanical properties. Being hydrophilic in nature, pineapple leaf fibers have very less affinity towards all types of polymer matrixes like HDPE, LDPE, PET, epoxy, etc. Surface treatments like alkaline treatment in different concentrations were conducted to improve its adhesion and compatibility towards hydrophobic polymer matrix i.e. epoxy resin. Pineapple leaf fiber epoxy composites have been prepared using hand layup method. Effect of fiber loading and surface treatments have been studied for different mechanical properties i.e. tensile strength, flexural strength and impact properties of pineapple leaf fiber composites. Analysis of fiber morphology has also been studied using FTIR, XRD. Scanning electron microscopy has also been used to study and compare the morphology of untreated and treated fibers. Also, the fracture surface has been reviewed comparing the reported literature of other eminent researchers of this field.

Keywords: composite, mechanical, natural fiber, pineapple leaf fiber

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Authors: Tanveer Iqbal, Saima Yasin, Muhammad Zafar, Ahmad Shakeel, Fahad Nazir, Paul F. Luckham

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The contact performance of polymeric composites is dependent on the localized mechanical properties of materials. This is particularly important for fiber oriented polymeric materials where self-lubrication from top layers has been the basic requirement. The nanoindentation response of fiber reinforced poly(etheretherketone), PEEK, composites have been evaluated to determine the near-surface mechanical characteristics. Load-displacement compliance, hardness and elastic modulus data based on contact compliance mode (CSM) indentation of carbon fiber oriented and glass fiber oriented PEEK composites are reported as a function of indentation contact displacement. The composite surfaces were indented to a maximum penetration depth of 5µm using Berkovich tip indenter. A typical multiphase response of the composite surface is depicted from analysis of the indentation data for the composites, showing presence of polymer matrix, fibers, and interphase regions. The observed experimental results show that although the surface mechanical properties of carbon fiber based PEEK composite were comparatively higher, the properties of matrix material were seen to be increased in the presence of glass fibers. The experimental methodology may provide a convenient means to understand morphological description of the multimodal polymeric composites.

Keywords: nanoindentation, PEEK, modulus, hardness, plasticization

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Authors: Jeevan Jyoti, Bhanu Pratap Singh, S. R. Dhakate

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In the present study, multiwalled carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) were synthesized by chemical vapor deposition and Improved Hummer’s method, respectively and their composite with acrylonitrile butadiene styrene (ABS) were prepared by twin screw co rotating extrusion technique. The electromagnetic interference (EMI) shielding effectiveness of graphene oxide carbon nanotube (GCNTs) hybrid composites was investigated and the results were compared with EMI shielding of carbon nanotube (CNTs) and reduced graphene oxide (RGO) in the frequency range of 12.4-18 GHz (Ku-band). The experimental results indicate that the EMI shielding effectiveness of these composites is achieved up to –21 dB for 10 wt. % loading of GCNT loading. The mechanism of improvement in EMI shielding effectiveness is discussed by resolving their contribution in absorption and reflection loss. The main reason for such a high improved shielding effectiveness has been attributed to the significant improvement in the electrical conductivity of the composites. The electrical conductivity of these GCNT/ABS composites was increased from 10-13 S/cm to 10-7 S/cm showing the improvement of the 6 order of the magnitude. Scanning electron microscopic (SEM) and high resolution transmission electron microscopic (HRTEM) studies showed that the GCNTs were uniformly dispersed in the ABS polymer matrix. GCNTs form a network throughout the polymer matrix and promote the reinforcement.

Keywords: ABS, EMI shielding, multiwalled carbon nanotubes, reduced graphene oxide, graphene, oxide-carbon nanotube (GCNTs), twin screw extruder, multiwall carbon nanotube, electrical conductivity

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Authors: Ahmed Hashim, Aseel Abdullah

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In this work, the fracture toughness of new green composite based on bio-PMMA resin reinforced with randomly short corn natural fiber of constant weight fraction by 10% wt was investigated. The corn fiber surface was modified by mercerization treatment with two different concentrations of sodium hydroxide (3, and 5% NaOH) for 1.5 and 3 hours respectively. The effect of mercerization treatment on the fracture behavior of the green composites was analyzed by FTIR spectra. NaOH concentration of 3% for 1.5 hrs. That was used for corn fiber green composite should the highest improvement in terms of plane strain fracture toughness KIC which increased by 62 % compared to untreated fiber composite material. On the other hand, increased both concentrations of alkali solution to 5% NaOH and time of soaking to 3 hrs. reduced the values of KIC lower than the value of the unfilled material.

Keywords: green composites, fracture toughness, corn natural fiber, bio-PMMA

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Authors: Sanam Haseen, Abdul Bari

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In this paper a three stage multivariate programming problem with random survey cost and variances as random variables has been formulated as a non-linear stochastic programming problem. The problem has been converted into an equivalent deterministic form using chance constraint programming and modified E-modeling. An empirical study of the problem has been done at the end of the paper using R-simulation.

Keywords: chance constraint programming, modified E-model, stochastic programming, stratified sample surveys, three stage sample surveys

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Authors: A. Merzouki, N. Haddaoui

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Polymers have a large reputation as electric insulators. These materials are characterized by weak weight, reduced price and a large domain of physical and chemical properties. They conquered new application domains that were until a recent past the exclusivity of metals. In this work, we used some composite materials (polymers/conductive fillers), as electrodes and we try to cover them with metallic lead layers in order to use them as courant collector grids in lead-acid battery plates.

Keywords: electrodeposition, polymer composites, carbon black, acetylene black

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Authors: Latha Nataraj, Todd Henry, Micheal Wallock, Asha Hall, Christine Hatter, Babak Anasori, Yury Gogotsi

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Multifunctional composites with enhanced strength and toughness for superior damage tolerance are essential for advanced aerospace and military applications. Detection of structural changes prior to visible damage may be achieved by incorporating fillers with tunable properties such as two-dimensional (2D) nanomaterials with high aspect ratios and more surface-active sites. While 2D graphene with large surface areas, good mechanical properties, and high electrical conductivity seems ideal as a filler, the single-atomic thickness can lead to bending and rolling during processing, requiring post-processing to bond to polymer matrices. Lately, an emerging family of 2D transition metal carbides and nitrides, MXenes, has attracted much attention since their discovery in 2011. Metallic electronic conductivity and good mechanical properties, even with increased polymer content, coupled with hydrophilicity make MXenes a good candidate as a filler material in polymer composites and exceptional as multifunctional damage indicators in composites. Here, we systematically study MXene-based (Ti₃C₂) coated on glass fibers for fiber reinforced polymer composite for self-sensing using microscopy and micromechanical testing. Further testing is in progress through the investigation of local variations in optical, acoustic, and thermal properties within the damage sites in response to strain caused by mechanical loading.

Keywords: damage sensing, fiber composites, MXene, self-sensing

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Authors: Nilgun Kuskonmaz, Zeynep Taslıcukur Ozturk, Cem Sahin

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In this study, Si3N4-SiC composites were synthesized by using different raw materials. In the first method, Si3N4 and C black powder mixtures were used to fabricate Si3N4-SiC composites by in-situ carbothermal reduction process. The percentage of C black was only changed. The effects of carbon black percentage in the mixtures were analysed by characterization of SiC particles which were obtained in the Si3N4 matrix. In the second method, SiC particles were added to the matrix in different weight ratios. The composites were pressed by cold isostatic method under 150 MPa pressure and pressureless sintered at 1700-1850 °C during 1 hour in the argon atmosphere. AlN and Y2O3 were used as sintering additives. Sintering temperature, time and all the effects on in-situ reaction were studied. The densification and microstructure properties of the produced ceramics were analysed. Density was one of the main subjects in these reactions. It is very important during porous SiC sintering. Green density and relative density were measured higher for CIP samples. Samples which were added carbon black were more porous than SiC added samples. The increase in the carbon black, makes increase in porosity. The outcome of the experiments was SiC powders which were obtained at the grain boundries of β-Si3N4 particles.

Keywords: silicon nitride, silicon carbide, carbon black, cold isostatic press, sintering

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Authors: Yasaman Samani, Ali Golmohammadi

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Introduction: The degree of conversion and depth of cure affects the clinical success of resin composite restorations directly. One of the main challenges in achieving a successful composite restoration is the achievement of sufficient depth of cure. The insufficient polymerization may lead to a decrease in the physical/mechanical and biological properties of resin composites and, as a result of that, unsuccessful composite restoration. Thus, because of the importance of studying and evaluating the depth of cure and degree of conversion in bulk-fill composites, we decided to evaluate and compare the degree of conversion and depth of cure in two bulk-fill composites; x-tra fill (Voco, Germany) and Opus Bulk fill APS (FGM, Brazil). Materials and Methods: Composite resin specimens (n=10) per group were prepared as cylinder blocks (4×8 mm) with bulk-fill composites, x-tra fil (Voco, Germany) designated as Group A, and Opus Bulk fill APS (FGM, Brazil) designated as Group B. Depth of cure was determined according to “ISO 4049; Depth of Cure” method, In which each specimen were cured (iLED, Woodpecker, China) 40 seconds and FTIR spectroscopy method was used to estimate the degree of conversion of both the bulk-fill composites. The degree of conversion of monomer to polymer was estimated individually in the coronal half (Group A1 and B1) and pulpal half (Group A2 and Group B2) by dividing each specimen into two halves. The data were analyzed using a Student’s t-test and one-way ANOVA at a 5% level of significance. Results: The mean depth of cure in x-tra fil (Voco, Germany) was 3.99 (±0.16), and for Opus Bulk fill, APS (FGM, Brazil) was 2.14 (±0.3). The degree of conversion percentage in Group A1 was 82.7 (±6.1), in group A2 was 73.4 (±5.2), in group B1 was 63.3 (±4.7) and in Group B2 was 56.5 (±7.7). Statistical analysis revealed a significant difference in the depth of cure between the two bulk-fill composites with x-tra fil (Voco, Germany) higher than Opus Bulk fill APS (FGM, Brazil) (P<0.001). The degree of conversion percentage also showed a significant difference, Group A1 being higher than A2 (P=0.0085), B1, and B2 (P<0.001). Group A2 was also higher than B1 (P=0.003) and B2 (P<0.001). There was no significant difference between B1 and B2 (P=0.072). Conclusion: The results indicate that x-tra fill has more depth of cure and a higher percentage of the degree of conversion than Opus Bulk fill APS. The coronal half of x-tra fil had the highest depth of cure percentage (82.66%), and the pulpal half of Opus Bulk fill APS had the lowest percentage (56.45%). Even though both bulk-fill composite materials had an acceptable degree of conversion (55% and higher), x-tra fill has shown better results.

Keywords: depth of cure, degree of conversion, bulk-fill composite, FTIR

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Authors: Nelson Bii, Christopher Ouma, John Odhiambo

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Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

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Authors: Dandi Bachtiar, Mohammed Ausama Abbas, Januar Parlaungan Siregar, Mohd Ruzaimi Bin Mat Rejab

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Short sugar palm fibre and thermoplastic polyurethane were combined to produce new composites by using the extrude method. Two techniques used to prepare a new composite material, firstly, extrusion of the base material with short fibre, secondly hot pressing them. The size of sugar palm fibre was fixed at 250µm. Different weight percent (10 wt%, 20 wt% and 30 wt%) were used in order to optimise preparation process. The optimization of process depended on the characterization mechanical properties such as impact, tensile, and flexural of the new (TPU/SPF) composite material. The results proved that best tensile and impact properties of weight additive fibre applied 10 wt%. There was an increasing trend recorded of flexural properties during increased the fibre loading. Meanwhile, the maximum tensile strength was 14.0 MPa at 10 wt% of the fibre. Moreover, there was no significant effect for additions more than 30 wt% of the fibre.

Keywords: composites, natural fibre, polyurethane, sugar palm

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Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

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Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

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Authors: Sudheer Kumar Gundati, Umasankar Patro

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Carbon nanotube (CNT) – polymer composites have been extensively studied due to their exceptional electrical and mechanical properties. In the present study, poly(vinylidene fluoride) (PVDF) – multi-walled CNT composites were prepared by melt-blending technique using pristine (ufCNT) and a modified dilute nitric acid-treated CNTs (fCNT). Due to this dilute acid-treatment, the fCNTs were found to show significantly improved dispersion and retained their electrical property. The fCNT showed an electrical percolation threshold (PT) of 0.15 wt% in the PVDF matrix as against 0.35 wt% for ufCNT. The composites were made into films of thickness ~0.3 mm by compression-molding and the resulting composite films were subjected to various property evaluations. It was found that the water contact angle (WCA) of the films increased with CNT weight content in composites and the composite film surface became hydrophobic (e.g., WCA ~104° for 4 wt% ufCNT and 111.5° for 0.5 wt% fCNT composites) in nature; while the neat PVDF film showed hydrophilic behavior (WCA ~68°). Significant enhancements in the mechanical properties were observed upon CNT incorporation and there is a progressive increase in the tensile strength and modulus with increase in CNT weight fraction in composites. The composite films were tested for strain-sensing applications. For this, a simple and non-destructive method was developed to demonstrate the strain-sensing properties of the composites films. In this method, the change in electrical resistance was measured using a digital multimeter by applying bending strain by oscillation. It was found that by applying dynamic bending strain, there is a systematic change in resistance and the films showed piezo-resistive behavior. Due to the high flexibility of these composite films, the change in resistance was reversible and found to be marginally affected, when large number of tests were performed using a single specimen. It is interesting to note that the composites with CNT content notwithstanding their type near the percolation threshold (PT) showed better strain-sensing properties as compared to the composites with CNT contents well-above the PT. On account of the excellent combination of the various properties, the composite films offer a great promise as strain-sensors for structural health-monitoring.

Keywords: carbon nanotubes, electrical percolation threshold, mechanical properties, poly(vinylidene fluoride), strain-sensor, water contact angle

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Authors: Deepika Sudevan, Patrick Rozycki, Laurent Gornet

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This paper presents the experimental identification of the fatigue limit for pristine and impacted Carbon Fiber Reinforced Epoxy polymer (CFRP) woven composites based on the relatively new self-heating methodology for composites. CFRP composites of [0/90]8 and quasi isotropic configurations prepared using hand-layup technique are subjected to low energy impacts (20 J energy) simulating a barely visible impact damage (BVID). Runway debris strike, tool drop or hailstone impact can cause a BVID on an aircraft fuselage made of carbon composites and hence understanding the post-impact fatigue response of CFRP laminates is of immense importance to the aerospace community. The BVID zone on the specimens is characterized using X-ray Tomography technique. Both pristine and impacted specimens are subjected to several blocks of constant amplitude (CA) fatigue loading keeping R-ratio a constant but with increments in the mean loading stress after each block. The number of loading cycles in each block is a subjective parameter and it varies for pristine and impacted CFRP specimens. To monitor the temperature evolution during fatigue loading, thermocouples are pasted on the CFRP specimens at specific locations. The fatigue limit is determined by two strategies, first is by considering the stabilized temperature in every block and second is by considering the change in the temperature slope per block. The results show that both strategies can be adopted to determine the fatigue limit in both pristine and impacted CFRP composites.

Keywords: CFRP, fatigue limit, low energy impact, self-heating, WRM

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Authors: Kevin Worrall, Euan McGookin

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The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: B. Z. Manuel, H. D. Esmeralda, H. S. Felipe, D. R. Héctor, D. de la Torre Sebastián, R. L. Diego

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Aluminum Matrix Composites reinforced with nanocrystalline Ni3Al carbon-coated intermetallic particles, were synthesized by powder metallurgy. Powder mixture of aluminum with 0.5-volume fraction of reinforcement particles was compacted by spark plasma sintering (SPS) technique and the compared with conventional sintering process. The better results for SPS technique were obtained in 520ºC-5kN-3min.The hardness (70.5±8 HV) and the elastic modulus (95 GPa) were evaluated in function of sintering conditions for SPS technique; it was found that the incorporation of these kind of reinforcement particles in aluminum matrix improve its mechanical properties. The densities were about 94% and 97% of the theoretical density. The carbon coating avoided the interfacial reaction between matrix-particle at high temperature (520°C) without show composition change either intermetallic dissolution.

Keywords: aluminum matrix composites, intermetallics, spark plasma sintering, nanocrystalline

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Authors: Yağmur Can Gündoğan, Kübra Gürcan Bayrak, Ece Özerdem, Buse Katipoğlu, Erhan Ayas, Rifat Yılmaz

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Eutectic oxide based ceramic matrix composites have a unique microstructure that does not include grain boundary in the form of a continuous network. Because of this, these materials have the properties of perfect high-temperature strength, creep strength, and high oxidation strength. Mechanical properties of them are much related to occurring solidification structures during eutectic reactions. One of the most important production methods of this kind of material is the process of vacuum arc melting. Within scope of this studying, it is aimed to investigate the production of Al₂O₃-YAG-based eutectic ceramics by Arc melting and Spark Plasma Sintering methods for use in aerospace and defense industries where high-temperature environments play an important role and to examine the effects of ZrO₂ and LiF additions on microstructure development and mechanical properties.

Keywords: alumina, composites, eutectic, YAG

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Mehmet Doğan, Mahir Alkan, Yasemin Turhan, Zürriye Gündüz, Pinar Beyli, Serap Doğan

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Advances and new discoveries in the field of the material science on the basis of technological developments have played an important role. Today, material science is branched the lower branches such as metals, nonmetals, chemicals, polymers. The polymeric nano composites have found a wide application field as one of the most important among these groups. Many polymers used in the different fields of the industry have been desired to improve the thermal stability. One of the ways to improve this property of the polymers is to form the nano composite products of them using different fillers. There are many using area of boron compounds and is increasing day by day. In order to the further increasing of the variety of using area of boron compounds and industrial importance, it is necessary to synthesis of nano-products and to find yourself new application areas of these products. In this study, PMMA/boronoxide nano composites were synthesized using solution intercalation, polymerization and melting methods; and PAA/boronoxide nano composites using solution intercalation method. Furthermore, rheological properties of nano composites synthesed according to melting method were also studied. Nano composites were characterized by XRD, FTIR-ATR, DTA/TG, BET, SEM, and TEM instruments. The effects of filler material amount, solvent types and mediating reagent on the thermal stability of polymers were investigated. In addition, the rheological properties of PMMA/boronoxide nano composites synthesized by melting method were investigated using High Pressure Capillary Rheometer. XRD analysis showed that boronoxide was dispersed in polymer matrix; FTIR-ATR that there were interactions with boronoxide between PAA and PMMA; and TEM that boronoxide particles had spherical structure, and dispersed in nano sized dimension in polymer matrix; the thermal stability of polymers was increased with the adding of boronoxide in polymer matrix; the decomposition mechanism of PAA was changed. From rheological measurements, it was found that PMMA and PMMA/boronoxide nano composites exhibited non-Newtonian, pseudo-plastic, shear thinning behavior under all experimental conditions.

Keywords: boronoxide, polymer, nanocomposite, rheology, characterization

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Authors: Liang-Hsuan Chen, Chia-Jung Chang

Abstract:

Fuzzy random variables have been introduced as an imprecise concept of numeric values for characterizing the imprecise knowledge. The descriptive parameters can be used to describe the primary features of a set of fuzzy random observations. In fuzzy environments, the expected values are usually represented as fuzzy-valued, interval-valued or numeric-valued descriptive parameters using various metrics. Instead of the concept of area metric that is usually adopted in the relevant studies, the numeric expected value is proposed by the concept of distance metric in this study based on two characters (fuzziness and randomness) of FRVs. Comparing with the existing measures, although the results show that the proposed numeric expected value is same with those using the different metric, if only triangular membership functions are used. However, the proposed approach has the advantages of intuitiveness and computational efficiency, when the membership functions are not triangular types. An example with three datasets is provided for verifying the proposed approach.

Keywords: fuzzy random variables, distance measure, expected value, descriptive parameters

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Authors: Hamed Khezrzadeh

Abstract:

Many investigations on the micromechanical structure of materials indicate that there exist fractal patterns at the micro scale in some of the main construction and industrial materials. A recently presented micro-fractal theory brings together the well-known periodic homogenization and the fractal geometry to construct an appropriate model for determination of the mechanical properties of particle reinforced composite materials. The proposed multi-step homogenization scheme considers the mechanical properties of different constituent phases in the composite together with the interaction between these phases throughout a step-by-step homogenization technique. In the proposed model the interaction of different phases is also investigated. By using this method the effect of fibers grading on the mechanical properties also could be studied. The theory outcomes are compared to the experimental data for different types of particle-reinforced composites which very good agreement with the experimental data is observed.

Keywords: fractal geometry, homogenization, micromehcanics, particulate composites

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Authors: Reza Pourjafar, Morteza Sohrabi-Gilani, Mostafa Jamshidi Avanaki, Malek Mohammad Ranjbar

Abstract:

Cementitious composites like concrete, are the most widely used materials in civil infrastructures. Numerous investigations on fiber’s effect on the properties of cement-based composites have been conducted in the last few decades. The use of fibers such as carbon nanofibers (CNFs) and carbon nanotubes (CNTs) in these materials is an ongoing field and needs further researches and studies. Excellent mechanical, thermal, and electrical properties of carbon nanotubes and nanofibers have motivated the development of advanced nanocomposites with outstanding and multifunctional properties. In this study, the electrical resistance of CNF reinforced cement mortar was examined. Three different dosages of CNF were used, and the resistances were compared to plain cement mortar. One of the biggest challenges in this study is dispersing CNF particles in the mortar mixture. Therefore, polycarboxylate superplasticizer and ultrasonication of the mixture have been selected for the purpose of dispersing CNFs in the cement matrix. The obtained results indicated that the electrical resistance of the CNF reinforced mortar samples decreases with increasing CNF content, which would be the first step towards examining strain and damage monitoring ability of cementitious composites containing CNF for structural health monitoring purposes.

Keywords: carbon nanofiber, cement and concrete, CNF reinforced mortar, smart mater, strain monitoring, structural health monitoring

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Authors: Hongmin Deng, Qionghua Wang

Abstract:

A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: chaos encryption, logistic map, pseudo-random sequence, RFID

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Authors: Bharatendra Rai

Abstract:

Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

Procedia PDF Downloads 287