Search results for: hybrid composite

Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Johannes Bibinger, Sebastian Eibl, Hans-Joachim Gudladt

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This study considers the influence of different irradiation scenarios on the thermal degradation of carbon fiber-reinforced polymers (CFRP). Real threats are simulated, such as fires with long-lasting low heat fluxes and nuclear heat flashes with short-lasting high heat fluxes. For this purpose, coated and uncoated quasi-isotropic samples of the commercially available CFRP HexPly® 8552/IM7 are thermally irradiated from one side by a cone calorimeter and a xenon short-arc lamp with heat fluxes between 5 and 175 W/cm² at varying time intervals. The specimen temperature is recorded on the front and backside as well as at different laminate depths. The CFRP is non-destructively tested with ultrasonic testing, infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), and micro-focused computed X-Ray tomography (μCT). Destructive tests are performed to evaluate the mechanical properties in terms of interlaminar shear strength (ILSS), compressive and tensile strength. The irradiation scenarios vary significantly in heat flux and exposure time. Thus, different heating rates, radiation effects, and temperature distributions occur. This leads to unequal decomposition processes, which affect the sensitivity of the strength type and damage behaviour of the specimens. However, with the use of surface coatings, thermal degradation of composite materials can be delayed.

Keywords: CFRP, one-sided thermal damage, high heat flux, heating rate, non-destructive and destructive testing

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Ambalika Ekka

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In today’s world, the growing demand for urban built forms has resulted in the production and consumption of building materials i.e. embodied energy in building construction, leading to pollution and greenhouse gas (GHG) emissions. Therefore, new buildings will offer a unique opportunity to implement more energy efficient building without compromising on building performance of the building. Embodied energy of building materials forms major contribution to embodied energy in buildings. The paper results in an approach towards designing an energy efficient apartment building through embodied energy assessment. This paper discusses the trend of residential development in Rourkela, which includes three case studies of the contemporary houses, followed by architectural elements, number of storeys, predominant material use and plot sizes using primary data. It results in identification of predominant material used and other characteristics in urban area. Further, the embodied energy coefficients of various dominant building materials and alternative materials manufactured in Indian Industry is taken in consideration from secondary source i.e. literature study. The paper analyses the embodied energy by estimating materials and operational energy of proposed building followed by altering the specifications of the materials based on the building components i.e. walls, flooring, windows, insulation and roof through res build India software and comparison of different options is assessed with consideration of sustainable parameters. This paper results that autoclaved aerated concrete block only reaches the energy performance Index benchmark i.e. 69.35 kWh/m² yr i.e. by saving 4% of operational energy and as embodied energy has no particular index, out of all materials it has the highest EE 23206202.43  MJ.

Keywords: energy efficient, embodied energy, EPI, building materials

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Authors: Chi-Chang Lin, Jiun-Yan Chiu

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Periodontal disease, oral cancer relating trauma is the prominent factor devastating bone tissue that is crucial to reestablishing in clinical. As we know, common symptom, osteoporosis, and infection limiting the ability of the bone tissue to recover cause difficulty before implantation therapy. Regeneration of bone tissue is the fundamental therapy before surgical processes. To promote the growth of bone tissue, many commercial products still have sophisticated problems that need to overcome. Regrettably, there is no available material which is apparently preferable for releasing and controlling of loading dosage, or mitigating inflammation. In our study, a hydrogel-based composite membrane has been prepared by using Gellan gum (GG), gamma-polyglutamic acid (γ-PGA) and glycerol with simple sol-gel method. GG is a natural material that is massively adopted in cartilage. Unfortunately, the strength of pure GG film is a manifest weakness especially under simulating body fluidic conditions. We utilize another biocompatible material, γ-PGA as cross-linker which can form tri-dimension structure that enhancing the strength. Our result indicated the strength of pure GG membrane can be obviously improved by cross-linked with γ-PGA (0.5, 0.6, 0.7, 0.8, 0.9, 1.0 w/v%). Besides, blending with glycerol (0, 1.0, 2.0, 3.0 w/v%) can significantly improve membrane toughness that corresponds to practical use. The innovative composited hydrogel made of GG, γ-PGA, and glycerol is attested with neat results including elongation and biocompatibility that take the advantage of extension covering major trauma. Recommendations are made for treatment to build up the foundation of bone tissue that would help patients to escape from the suffering and shorten the amount of time in recovery.

Keywords: bone tissue, gellan gum, regeneration, toughness

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

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Authors: Arpan Bera, Rini Ganguly, Raja Chakraborty, Amlan J. Pal

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To deal with the increasing demands for the high-density non-volatile memory devices, we need nano-sites with efficient and stable charge storage capabilities. We prepared nanocrystals (NCs) of inorganic perovskite, CsPbCl₃ coated with Cs₄PbCl₆, by colloidal synthesis. Due to the type-I band alignment at the junction, this core-shell composite is expected to behave as a charge trapping site. Using Scanning Tunneling Spectroscopy (STS), we investigated voltage-controlled resistive switching in this heterostructure by tracking the change in its current-voltage (I-V) characteristics. By applying voltage pulse of appropriate magnitude on the NCs through this non-invasive method, different resistive states of this system were systematically accessed. For suitable pulse-magnitude, the response jumped to a branch with enhanced current indicating a high-resistance state (HRS) to low-resistance state (LRS) switching in the core-shell NCs. We could reverse this process by using a pulse of opposite polarity. These two distinct resistive states can be considered as two logic states, 0 and 1, which are accessible by varying voltage magnitude and polarity. STS being a local probe in space enabled us to capture this switching at individual NC site. Hence, we claim a bright prospect of these core-shell NCs made of inorganic halide perovskites in future high density memory application.

Keywords: Core-shell perovskite, CsPbCl₃-Cs₄PbCl₆, resistive switching, Scanning Tunneling Spectroscopy

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Authors: Yogesh Mahor, Subhash Nigam, Abhai Khare

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Road safety education is a composite subject which should be viewed holistically if taken into accoubehavior change communication, safe road infrastructure and low enforcement. Specific and customized road safety education is crucial for each type of road user and learners in the formal and informal teaching and various kind of training programs directly sponsored by state and center government, as they are active contributors to shaping a community and responsible citizens. The aim of this discussion article is to explore a strategy to integrate road safety education into the formal curriculum of schools, higher education institutions, driving schools, skill development centers, various government funded urban and rural development training institutions and their work plans as standing agenda. By applying the desktop research method, the article conceptualizes what the possible focus of road safety education and training should be. The article then explores international common practices in road safety education and training, and considers the necessary synergy between education, road engineering and low enforcement. The article uses secondary data collected from documents which are then analysed in a sectoral way. A well-designed road safety strategy for mainstreaming education and government-sponsored training is urgently needed, facilitating partnerships in various sectors to implement such education in the students and learners in multidisciplinary ways.

Keywords: road safety education, curriculum-based road safety education, behavior change communication, low enforcement, road engineering, safe system approach, infrastructure development consultants

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

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Authors: Eunice Oluwayemisi Adeparusi, Mary Adedolapo Ijadeyila

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The study was carried out at the Federal University of Technology, Akure, Nigeria, West Africa. Seven set of diets were prepared comprising of two sets. The first set consisted of a combination of three diets from a combination of two different citrus peels from Orange (Citrus sinesis), Tangerine (Citrus tangerina / Citrus reticulata) and Tangelo (Citrus tangelo a hybrid of Citrus reticulata and Citrus maxima) at 50:50 while the other three consisted f50:50. Diet with 100% vitamin premix served as the control. Air-dried citrus peels were added in a 40% crude protein diet for the juveniles (4.49±0.05g) Clarias gariepinus. The experiment was carried out for a period of 56 days in triplicate trials. Fish were randomly distributed into twenty-one tanks at ten fish per tanks. The feed was extruded and fed to satiation twice daily. The result shows that fish fed Tangelo and Tangerine (TGL-TGR) had the best growth response in terms of final weight, specific growth rate, feed conversion ratio and feed utilization efficiency when compared with other diets. The FCR of fish in the diet ranges from 0.93-1.62. Fish fed the mixture of Orange peel and Vitamin-mineral premix (ORG-VIT) and those on Tangelo and Vitamin-mineral premix (TGL-VIT) had higher survival rate. There were significant differences (P<0.05) in the mean final weight, weight gain and specific growth rate. The result shows that citrus peels enhance the growth performance and feed utilization of the juvenile of African mud catfish, thereby reducing the cost of fish production.

Keywords: African mud catfish, growth, citrus peels, vitamin-mineral premix, nutrient utilization, additives

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

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Three preceramic polymer formulations for potential use in 3D printing technologies were investigated. The polymeric precursors include an allyl hydrido polycarbosilane (SMP-10), SMP-10/1,6-dexanediol diacrylate (HDDA) mixture, and polydimethylsiloxane (PDMS). The rheological property of the polymeric precursors, including the viscosity within a wide shear rate range was compared to determine the applicability in additive manufacturing technology. The structural properties of the polymeric solutions and their photocureability were investigated using Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Moreover, thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were utilized to study polymeric to ceramic conversion for versatile precursors. The prepared precursor resin proved to have outstanding photo-curing properties and the ability to transform to the silicon carbide phase at temperatures as low as 850 °C. The obtained ceramic was fully dense with nearly linear shrinkage and a shiny, smooth surface after pyrolysis. Furthermore, after pyrolysis to 1350 °C and TGA analysis, PDMS polymer showed the highest onset decomposition temperature and the lowest retained weight (52 wt%), while SMP.10/HDDA showed the lowest onset temperature and ceramic yield (71.7 wt%). In terms of crystallography, the ceramic matrix composite appeared to have three coexisting phases, including silicon carbide, and silicon oxycarbide. The results are very promising to fabricate ceramic materials working at high temperatures with complex geometries.

Keywords: preceramic polymer, silicon carbide, photocuring, allyl hydrido polycarbosilane, SMP-10

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Yan Liu

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The Gini coefficient indicates that the inequality of income distribution is rising in China. How individuals viewing the equality of current society is an important predicator of social turbulence. Perceptions of social justice may vary according to the social stratification. People usually use socioeconomic status to identify divisions between social stratifications. The objective of this study is to explore the potential influence of socioeconomic status on citizens’ perceptions of social justice in China. Socioeconomic status (SES) is usually reflected by either an SES indicator or a composite of three core dimensions: education, income and occupation. With data collected in the 2010 Chinese General Social Survey (CGSS), this study uses OLS regression analyses to examine the relationship between socioeconomic status (SES) and citizens’ perceptions of social justice. This study finds that most Chinese citizens believe that the current society is fair or more than fair. Socioeconomic status (SES) has a positive impact on citizens’ perceptions of social justice, which means individuals with higher indicator of socioeconomic status prefer to believe current society is fair. However, the three core dimensions which are used to measure socioeconomic status (SES) have different influences on perceptions of social justice: First, income helps enhance citizens’ sense of social justice. Second, education weakens citizens’ sense of social justice. Third, compared to the middle occupational status, people of both higher occupational status and lower occupational status have higher levels of perceptions of social justice. Though education creates a negative influence on perceptions of social justice, its effect is much weaker than that of income, which indicates income is a determining factor for enhancing people’s perceptions of social justice in China’s market society. Policy implications are discussed.

Keywords: education, income, occupation, perceptions of social justice, social stratification, socioeconomic status

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Authors: Ricardo Mendoza, Jason Briceño, Juan F. Santa, Gabriel Peluffo, Mauricio Márquez, Beatriz Cardozo, Carlos Gutiérrez

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The most common controlled method to obtain impact strength of composites materials is performing a Charpy Impact Test which consists of a pendulum with calibrated mass and length released from a known height. In fact, composites components experience impact events in normal operations such as when a tool drops or a foreign object strikes it. These events are categorized into low velocity impact (LVI) which typically occurs at velocities below 10m/s. In this study, the major aim was to calculate the absorbed energy during the impact. Tests were performed on three types of composite panels: fiberglass laminated panels, coir fiber reinforced polyester and coir fiber reinforced polyester subjected to water immersion for 48 hours. Coir fibers were obtained in local plantations of the Caribbean coast of Colombia. They were alkali treated in 5% aqueous NaOH solution for 2h periods. Three type of shape impactors were used on drop-weight impact test including hemispherical, ogive and pointed. Failure mechanisms and failure modes of specimens were examined using an optical microscope. Results demonstrate a reduction in absorbed energy correlated with the increment of water absorption of the panels. For each level of absorbed energy, it was possible to associate a different fracture state. This study compares results of energy absorbed obtained from two impact test methods.

Keywords: coir fiber, polyester composites, low velocity impact, Charpy impact test, drop-weight impact test

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Authors: Naghmeh Zamani, Ashkan Pourkand, David Grow

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This paper presents the design and mechanical model of a hybrid impedance/admittance haptic device optimized for applications, like bone drilling, spinal awl probe use, and other surgical techniques were high force is required in the tool-axial direction, and low impedance is needed in all other directions. The performance levels required cannot be satisfied by existing, off-the-shelf haptic devices. This design may allow critical improvements in simulator fidelity for surgery training. The device consists primarily of two low-mass (carbon fiber) plates with a rod passing through them. Collectively, the device provides 6 DOF. The rod slides through a bushing in the top plate and it is connected to the bottom plate with a universal joint, constrained to move in only 2 DOF, allowing axial torque display the user’s hand. The two parallel plates are actuated and located by means of four cables pulled by motors. The forward kinematic equations are derived to ensure that the plates orientation remains constant. The corresponding equations are solved using the Newton-Raphson method. The static force/torque equations are also presented. Finally, we present the predicted distribution of location error, cables velocity, cable tension, force and torque for the device. These results and preliminary hardware fabrication indicate that this design may provide a revolutionary approach for haptic display of many surgical procedures by means of an architecture that allows arbitrary workspace scaling. Scaling of the height and width can be scaled arbitrarily.

Keywords: cable direct driven robot, haptics, parallel plates, bone drilling

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Authors: Elvira Hörandl

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The term “Geographical parthenogenesis” describes the phenomenon that asexual organisms usually occupy larger and more northern distribution areas than their sexual relatives and tend to colonize previously glaciated areas. Several case studies in flowering plants confirm the geographical pattern, but the causal factors behind the phenomenon are still unclear. Previous authors regarded predominant polyploidy in asexual (apomictic) plants as the main factor. However, the geographical pattern is not the rule for sexual polyploids. Recent research confirmed a previous hypothesis of the author that a combination of factors is acting: Although uniparental reproduction provides better colonization abilities, it is most efficient in combination with polyploidy. I will present results on case studies in the genus Ranunculus of both autopolyploid and allopolyploid species and species complexes reproducing via facultative apomixis. Polyploidy seems to contribute mainly to a better tolerance of colder climates and temperate extremes, whereby epigenetic flexibility, changes in gene expression, and phenotypic plasticity play an important role in occupying ecological niches under harsh conditions. Phylogenomic studies entangle complex hybrid origins of asexual taxa, which increases intragenomic heterozygosity of asexual plants. Interestingly, our results suggest an association of sexuality with abiotic stresses, specifically with light stress, which might explain that still, most plants in high altitudes and in southern areas retain sexual reproduction despite other climatic conditions that would favor apomictic plants. We conclude that geographical parthenogenesis results from the complex interplay of the genomic constitution, mode of reproduction and environmental factors.

Keywords: apomixis, polyploidy, hybridization, abiotic stress, epigenetics, phylogenomics

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Authors: J. Samuel, S. Al-Enezi, A. Al-Banna

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High-density polyethylene reinforced with carbon nanofibers (HDPE/CNF) have been prepared via melt processing using dialkylimidazolium tetrafluoroborate (ionic liquid) as a dispersion agent. The prepared samples were characterized by thermogravimetric (TGA) and differential scanning calorimetric (DSC) analyses. The samples blended with imidazolium ionic liquid exhibit higher thermal stability. DSC analysis showed clear miscibility of ionic liquid in the HDPE matrix and showed single endothermic peak. The melt rheological analysis of HDPE/CNF composites was performed using an oscillatory rheometer. The influence of CNF and ionic liquid concentration (ranging from 0, 0.5, and 1 wt%) on the viscoelastic parameters was investigated at 200 °C with an angular frequency range of 0.1 to 100 rad/s. The rheological analysis shows the shear-thinning behavior for the composites. An improvement in the viscoelastic properties was observed as the nanofiber concentration increases. The progress in the modulus values was attributed to the structural rigidity imparted by the high aspect ratio CNF. The modulus values and complex viscosity of the composites increased significantly at low frequencies. Composites blended with ionic liquid exhibit slightly lower values of complex viscosity and modulus over the corresponding HDPE/CNF compositions. Therefore, reduction in melt viscosity is an additional benefit for polymer composite processing as a result of wetting effect by polymer-ionic liquid combinations.

Keywords: high-density polyethylene, carbon nanofibers, ionic liquid, complex viscosity

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Authors: Matthias Banholzer, Hagen Müller, Michael Pfitzner

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Gas internal combustion engines are widely used as propulsion systems or in power plants to generate heat and electricity. While there are different types of injection methods including the manifold port fuel injection and the direct injection, the latter has more potential to increase the specific power by avoiding air displacement in the intake and to reduce combustion anomalies such as backfire or pre-ignition. During the opening process of the injector, multiple flow regimes occur: subsonic, transonic and supersonic. To cover the wide range of Mach numbers a compressible pressure-based solver is used. While the standard Pressure Implicit with Splitting of Operators (PISO) method is used for the coupling between velocity and pressure, a high-resolution non-oscillatory central scheme established by Kurganov and Tadmor calculates the convective fluxes. A blending function based on the local Mach- and CFL-number switches between the compressible and incompressible regimes of the developed model. As the considered operating points are well above the critical state of the used fluids, the ideal gas assumption is not valid anymore. For the real gas thermodynamics, the models based on the Soave-Redlich-Kwong equation of state were implemented. The caloric properties are corrected using a departure formalism, for the viscosity and the thermal conductivity the empirical correlation of Chung is used. For the injector geometry, the dimensions of a diesel injector were adapted. Simulations were performed using different nozzle and needle geometries and opening curves. It can be clearly seen that there is a significant influence of all three parameters.

Keywords: high pressure gas injection, hybrid solver, hydrogen injection, needle opening process, real-gas thermodynamics

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Authors: László Forró

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The organolead halide perovskite CH3NH3PbI3 and its derivatives are known to be very efficient light harvesters revolutionizing the field of solid-state solar cells. The major research area in this field is photovoltaic device engineering although other applications are being explored, as well. Recently, we have shown that nanowires of this photovoltaic perovskite can be synthesized which in association with carbon nanostructures (carbon nanotubes and graphene) make outstanding composites with rapid and strong photo-response. They can serve as conducting electrodes, or as central components of detectors. The performance of several miniature devices based on these composite structures will be demonstrated. Our latest findings on the guided growth of perovskite nanowires by solvatomorph graphoepitaxy will be presented. This method turned out to be a fairly simple approach to overcome the spatially random surface nucleation. The process allows the synthesis of extremely long (centimeters) and thin (a few nanometers) nanowires with a morphology defined by the shape of nanostructured open fluidic channels. This low-temperature solution-growth method could open up an entirely new spectrum of architectural designs of organometallic-halide-perovskite-based heterojunctions and tandem solar cells, LEDs and other optoelectronic devices. Acknowledgment: This work is done in collaboration with Endre Horvath, Massimo Spina, Alla Arakcheeva, Balint Nafradi, Eric Bonvin1, Andrzej Sienkievicz, Zsolt Szekrenyes, Hajnalka Tohati, Katalin Kamaras, Eduard Tutis, Laszlo Mihaly and Karoly Holczer The research is supported by the ERC Advanced Grant (PICOPROP670918).

Keywords: photovoltaics, perovskite, nanowire, photodetector

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Authors: Jing Yuan, Hongwei Yang

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This paper aims to understand U.S. middle school students’ mathematics achievements by examining relevant student and school-level predictors. Through a variance component analysis, the study first identifies evidence supporting the use of multilevel modeling. Then, a multilevel analysis is performed under Bayesian statistical inference where prior information is incorporated into the modeling process. During the analysis, independent variables are entered sequentially in the order of theoretical importance to create a hierarchy of models. By evaluating each model using Bayesian fit indices, a best-fit and most parsimonious model is selected where Bayesian statistical inference is performed for the purpose of result interpretation and discussion. The primary dataset for Bayesian modeling is derived from the Program for International Student Assessment (PISA) in 2012 with a secondary PISA dataset from 2003 analyzed under the traditional ordinary least squares method to provide the information needed to specify informative priors for a subset of the model parameters. The dependent variable is a composite measure of mathematics literacy, calculated from an exploratory factor analysis of all five PISA 2012 mathematics achievement plausible values for which multiple evidences are found supporting data unidimensionality. The independent variables include demographics variables and content-specific variables: mathematics efficacy, teacher-student ratio, proportion of girls in the school, etc. Finally, the entire analysis is performed using the MCMCpack and MCMCglmm packages in R.

Keywords: Bayesian multilevel modeling, mathematics education, PISA, multilevel

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Authors: Moaine Jebara, Lionel Boillereaux, Sofiane Belhabib, Michel Havet, Alain Sarda, Pierre Mousseau, Rémi Deterre

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Energy consumption efficiency is a major concern for the material processing industry such as thermoforming process and molding. Indeed, these systems should deliver the right amount of energy at the right time to the processed material. Recent technical development, as well as the particularities of the heating system dynamics, made the Model Predictive Control (MPC) one of the best candidates for thermal control of several production processes like molding and composite thermoforming to name a few. The main principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process which allows the current timeslot to be optimized while taking future timeslots into account. This study presents a procedure based on a predictive control that brings balance between optimality, simplicity, and flexibility of its implementation. The development of this approach is progressive starting from the case of a single zone before its extension to the multizone and/or multisource case, taking thus into account the thermal couplings between the adjacent zones. After a quadratic formulation of the MPC criterion to ensure the thermal control, the linear expression is retained in order to reduce calculation time thanks to the use of the ARMAX linear decomposition methods. The effectiveness of this approach is illustrated by experiment and simulation.

Keywords: energy efficiency, linear decomposition methods, model predictive control, mold heating systems

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Authors: Vishal Mahale, Jayashree Bijwe, Sujeet K. Sinha

Abstract:

Nowadays extensive research is going on in the field of friction materials (FMs) for development of eco-friendly brake-materials by removing copper as it is a proven threat to the aquatic organisms. Researchers are keen to find the solution for copper-free FMs by using different metals or without metals. Steel wool is used as a reinforcement in non-asbestos organic (NAO) FMs mainly for increasing thermal conductivity, and it affects wear adversely, most of the times and also adds friction fluctuations. Copper and brass used to be the preferred choices because of superior performance in almost every aspect except cost. Since these are being phased out because of a proven threat to the aquatic life. Keeping this in view, a series of realistic multi-ingredient FMs containing stainless steel (SS) swarfs as a theme ingredient in increasing amount (0, 5, 10 and 15 wt. %- S₅, S₁₀, and S₁₅) were developed in the form of brake-pads. One more composite containing copper instead of SS swarfs (C₁₀) was developed. These composites were characterized for physical, mechanical, chemical and tribological performance. Composites were tribo-evaluated on a chase machine with various test loops as per SAE J661 standards. Various performance parameters such as normal µ, hot µ, performance µ, fade µ, recovery µ, % fade, % recovery, wear resistance, etc. were used to evaluate the role of amount of SS swarfs in FMs. It was concluded that SS swarfs proved successful in Cu replacement almost in all respects except wear resistance. With increase in amount of SS swarfs, most of the properties improved. Worn surface analysis and wear mechanism were studied using SEM and EDAX techniques.

Keywords: Chase type friction tester, copper-free, non-asbestos organic (NAO) friction materials, stainless steel swarfs

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Authors: Navid Eghtedarpour, Mohammad Reza Hasani

Abstract:

Since renewable wind power plants are usually installed in mountain regions and high-level lands, they are often prone to lightning strikes and their hazardous effects. Although the transmission line is protected using guard wires in order to prevent the lightning surges to strike the phase conductors, the back-flashover may also occur due to tower footing resistance. A combination of back-flashover corrective methods, tower-footing resistance reduction, insulation level improvement, and line arrester installation, are analyzed in this paper for back-flashover rate reduction of a double-circuit 63 kV line in the south region of Fars province. The line crosses a mountain region in some sections with a moderate keraunic level, whereas tower-footing resistance is substantially high at some towers. Consequently, an exceptionally high back-flashover rate is recorded. A new method for insulation improvement is studied and employed in the current study. The method consists of using a composite-type creepage extender in the string. The effectiveness of this method for insulation improvement of the string is evaluated through the experimental test. Simulation results besides monitoring the one-year operation of the 63-kV line show that due to technical, practical, and economic restrictions in operated sub-transmission lines, a combination of corrective methods can lead to an effective solution for the protection of transmission lines against lightning.

Keywords: lightning protection, BF rate, grounding system, insulation level, line surge arrester

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Authors: Jan Dahlhaus, Alejandro Cardenas Miranda, Frederik Scholer, Maximilian Leonhardt, Matthias Moullion, Frank Beutenmuller, Julia Eckhardt, Josef Wasner, Frank Nittel, Sebastian Stoll, Devin Atukalp, Daniel Folgmann, Tobias Mayer, Obrad Dordevic, Paul Riley, Jean-Marc Le Peuvedic

Abstract:

Electrical and hybrid aerospace technologies pose very challenging demands on the battery pack – especially with respect to weight and power. In the Clean Sky 2 research project LiBAT (funded by the EU), the consortium is currently building an ambitious prototype with state-of-the art cells that shows the potential of an intelligent pack design with a high level of integration, especially with respect to thermal management and power electronics. For the latter, innovative multi-level-inverter technology is used to realize the required power converting functions with reduced equipment. In this talk the key approaches and methods of the LiBat project will be presented and central results shown. Special focus will be set on the simulative methods used to support the early design and development stages from an overall system perspective. The applied methods can efficiently handle multiple domains and deal with different time and length scales, thus allowing the analysis and optimization of overall- or sub-system behavior. It will be shown how these simulations provide valuable information and insights for the efficient evaluation of concepts. As a result, the construction and iteration of hardware prototypes has been reduced and development cycles shortened.

Keywords: electric aircraft, battery, Li-ion, multi-level-inverter, Novec

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Authors: C. Busuioc, G. Voicu, S. I. Jinga

Abstract:

The field of tissue engineering brings new challenges in terms of proposing original solutions for ongoing medical issues, improving the biological performances of existing clinical systems and speeding the healing process for a faster recovery and a more comfortable life as patient. In this context, we propose the obtaining of 3D porous scaffolds of mineral nature, dedicated to bone repairing and regeneration purposes or employed as bioactive filler for bone cements. Thus, bacterial cellulose - calcium phosphates composite materials have been synthesized by successive immersing of the polymeric membranes in the precursor solution containing Ca2+ and [PO4]3- ions. The mineral phase deposited on the surface of biocellulose fibers was varied as amount through the number of immersing cycles. The intermediary composites were subjected to thermal treatments at different temperatures in order to remove the organic part and provide the formation of a self-sustained 3D architecture. The resulting phase composition consists of common phosphates, while the morphology largely depends on the preparation parameters. Thus, the aspect of the 3D mineral scaffolds can be tuned from a loose microstructure composed of large grains connected via monocrystalline nanorods to a trabecular pattern crossed by parallel internal channels, just like the natural bone. The bioactivity and biocompatibility of the obtained materials have been also assessed, with encouraging results in the clinical use direction. In conclusion, the compositional, structural, morphological and biological characterizations sustain the suitability of the reported biostructures for integration in hard tissue engineering applications.

Keywords: bacterial cellulose, bone reconstruction, calcium phosphates, mineral scaffolds

Procedia PDF Downloads 169

Authors: Minbale Aschale, Bitew K. Dessie, Endaweke Assegide, Yosef Abebe, Tena Alamirew, Claire L. Walsh, Gete Zeleke

Abstract:

The upper Awash Basin faces pollution challenges due to urbanization, population growth, and expanding industries. It receives various pollutants from its catchments. The study aimed to assess the impact of wastewater irrigation on vegetables and inform stakeholders about pollution challenges and consequences. Eighty-two composite samples of matured vegetables were randomly collected from twenty-one agricultural farm sites. These samples were analyzed for potentially toxic elements, including Cd, Pb, Cr, Hg, As, Ni, Sr, B, Co, Cu, Mn, Fe, Zn, and Se. The results indicated significant variations in concentrations across different sites, with localized contributions from various contaminants. Cr, Cd, and Pb concentrations in most vegetables exceeded recommended levels. Pollution levels varied with metals and vegetable types. Different vegetables contribute differently to health risks. The relative contributions of Ethiopian kale, cabbage, red beet, lettuce, Swiss chard, Gurage cabbage, tomato, zucchini, carrot, onion, watermelon, and potato to the aggregated risk were 12.69%, 12.25%, 11.83%, 11.20%, 10.21%, 9.91%, 8.49%, 5.66%, 3.96%, 3.35%, 3.10%, and 2.72%, respectively. Comparison with permissible standards revealed inadequate environmental management by relevant regulatory bodies and industries. Despite good laws and standards at the federal and regional levels, they are ineffectively implemented or enforced to prevent environmental pollution. Mitigation measures are urgently recommended to address the potential health implications of toxic substances.

Keywords: pollution, upper Awash Basin, health risk, Ethiopia

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Authors: Muhamad Sani Buang, Shahrul Azam Abdullah, Juri Saedon

Abstract:

There is not much effective guideline on development of design parameters selection on springback for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for springback in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in U-channel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on springback of flange angle (β2) and wall opening angle (β1), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the springback behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for springback was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values

Keywords: advance high strength steel, u-channel process, springback, design of experiment, optimization, response surface methodology (rsm)

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

Abstract:

The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

Procedia PDF Downloads 337