Search results for: mechanical modeling

Authors: Abhishek Saha, Serene Tay, Gerard Pijcke

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The availability of high-resolution topography and rainfall information in urban areas has made it necessary to revise modeling approaches used for simulating flood risk assessments. Lidar derived elevation models that have 1m or lower resolutions are becoming widely accessible. The classical approaches of 1D-2D flow models where channel flow is simulated and coupled with a coarse resolution 2D overland flow models may not fully utilize the information provided by high-resolution data. In this context, a study was undertaken to compare three different modeling approaches to simulate flooding in an urban area. The first model used is the base model used is Sobek, which uses 1D model formulation together with hydrologic boundary conditions and couples with an overland flow model in 2D. The second model uses a full 2D model for the entire area with shallow water equations at the resolution of the digital elevation model (DEM). These models are compared against another shallow water equation solver in 2D, which uses a subgrid method for grid refinement. These models are simulated for different horizontal resolutions of DEM varying between 1m to 5m. The results show a significant difference in inundation extents and water levels for different DEMs. They are also sensitive to the different numerical models with the same physical parameters, such as friction. The study shows the importance of having reliable field observations of inundation extents and levels before a choice of model and data can be made for spatial flood risk assessments.

Keywords: flooding, DEM, shallow water equations, subgrid

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Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

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Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

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Authors: Chi-Yuan Huang, Mei-Chuan Kuo, Ching-Yi Hsiao

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In this study, acids with various chain lengths (C₆, C₈, C₁₀ and C₁₂) modified by methane sulfonic acid (MSA) and temperature were used to modify tapioca starch (TPS), then the glycerol (GA) were added into modified starch, to prepare new blends. The mechanical properties, thermal properties and physical properties of blends were studied. This investigation was divided into two parts.  First, the biodegradable materials were used such as starch and glycerol with hexanedioic acid (HA), suberic acid (SBA), sebacic acid (SA), decanedicarboxylic acid (DA) manufacturing with different temperatures (90, 110 and 130 °C). And then, the solution was added into modified starch to prepare the blends by using single-screw extruder. The FT-IR patterns indicated that the characteristic peak of C=O in ester was observed at 1730 cm^-1. It is proved that different chain length acids (C₆, C₈, C₁₀ and C₁₂) reacted with glycerol by esterification and these are used to plasticize blends during extrusion. In addition, the blends would improve the hydrolysis and thermal stability. The water contact angle increased from 43.0° to 64.0°.  Second, the HA (110 °C), SBA (110 °C), SA (110 °C), and DA blends (130 °C) were used in study, because they possessed good mechanical properties, water resistances and thermal stability. On the other hand, the various contents (0, 0.005, 0.010, 0.020 g) of MSA were also used to modify the mechanical properties of blends. We observed that the blends were added to MSA, and then the FT-IR patterns indicated that the C=O ester appeared at 1730 cm^-1. For this reason, the hydrophobic blends were produced. The water contact angle of the MSA blends increased from 55.0° to 71.0°. Although break elongation of the MSA blends reduced from the original 220% to 128%, the stress increased from 2.5 MPa to 5.1 MPa. Therefore, the optimal composition of blends was the DA blend (130 °C) with adding of MSA (0.005 g).

Keywords: chain length acids, methane sulfonic acid, Tapioca starch (TPS), tensile stress

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Authors: Collins Chike Kwasi-Effah, Timon Rabczuk, Osarobo O. Ighodaro

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The energy density of various battery technologies used in the electric vehicle industry still ranges between 250 Wh/kg to 650 Wh/kg, thus limiting their distance range compared to the conventional internal combustion engine vehicle. In order to overcome this limitation, a new material technology is necessary to overcome this limitation. The proposed sole lithium-air battery seems to be far behind in terms of practical implementation. In this paper, experimental analysis using COMSOL multiphysics has been conducted to predict the performance of lithium ion battery with variation in the elastic property of five different cathode materials including; LiMn2O4, LiFePO4, LiCoO2, LiV6O13, and LiTiS2. Combining LiCoO2, and aqueous lithium showed great improvement in the energy density. Thus, the material combination of LiCoO2/aqueous lithium-air could give a practical solution in achieving high energy density for application in the electric vehicle industry.

Keywords: battery energy, energy density, lithium-ion, mechanical property

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Authors: Haydar S. Al Shabbani, M. Marshall, R. Goodall

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Metal matrix composites (MMCs) have been explored for many applications for many decades. Recently, this includes investigations for thermal applications associated with electronics, such as in heat sinks. Here, to promote thermal conductivity, composites of a metal matrix with diamond particles are used. However, this class of composites has not yet been extensively examined for mechanical and tribological behavior, especially for applications that require extreme mechanical and tribological strength, such as the resistance to abrasive cutting. Therefore, this research seeks to develop a composite material with metal matrix and diamond particles which resist abrasive and cutting forces. The development progresses through a series of steps, exploring methods to process the material, understanding the mechanics of abrasive behavior and optimizing the composite structure to resist abrasive cutting. In processing, infiltration casting under gas pressure has been applied to molten aluminum to obtain a significant penetration of the metal into a preform of diamond particles. Different diamond particle sizes were used with different surface modifications (coated/uncoated), and to compare resulting composites with the same particle sizes. Al-1 wt.% Mg as a matrix alloy was utilised to investigate the possible effect of Mg on bonding phases during the infiltration process. The mechanical behavior and microstructure of the materials produced have been characterised. These tests showed that the surface modification of the diamond particles with a reactive material (Ti-coating) has an important role for enhancing the bonding between the aluminium matrix and diamond reinforcement as apparent under SEM observation. The effect of this improved bond is seen in the cutting resistance of the material.

Keywords: aluminium, composites, diamond, Ti-coated, tribology

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Authors: Shu Tao

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Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

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Authors: Sina Keyhanian, Abbas Ahmadi, Behrooz Karimi

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We present a multi-objective binary programming model which considers surgical cases are scheduling among operating rooms and the configuration of surgical instruments in limited capacity hospital trays, simultaneously. Many mathematical models have been developed previously in the literature addressing different challenges in health-care logistics such as assigning operating rooms, leveling beds, etc. But what happens inside the operating rooms along with the inventory management of required instruments for various operations, and also their integration with surgical scheduling have been poorly discussed. Our model considers the minimization of movements between trays during a surgery which recalls the famous cell formation problem in group technology. This assumption can also provide a major potential contribution to robotic surgeries. The tray configuration problem which consumes surgical instruments requirement plan (SIRP) and sequence of surgical procedures based on required instruments (SIRO) is nested inside the bin packing problem. This modeling approach helps us understand that most of the same-output solutions will not be necessarily identical when it comes to the rearrangement of surgeries among rooms. A numerical example has been dealt with via a proposed nested simulated annealing (SA) optimization approach which provides insights about how various configurations inside a solution can alter the optimal condition.

Keywords: health-care logistics, hospital tray configuration, off-line bin packing, simulated annealing optimization, surgical case scheduling

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications

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Authors: Ali Mirtaghavi, Andy Baldwin, Rajendarn Muthuraj, Jack Luo

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Recent advances in biomaterials have led to utilizing biopolymers to develop 3D scaffolds in tissue regeneration. One of the major challenges of designing biomaterials for 3D scaffolds is to mimic the building blocks similar to the extracellular matrix (ECM) of the native tissues. Biopolymer based aerogels obtained by freeze-drying have shown to provide structural similarities to the ECM owing to their 3D format and a highly porous structure with interconnected pores, similar to the ECM. Gelatin (GEL) is known to be a promising biomaterial with inherent regenerative characteristics owing to its chemical similarities to the ECM in native tissue, biocompatibility abundance, cost-effectiveness and accessible functional groups, which makes it facile for chemical modifications with other biomaterials to form biocomposites. Despite such advantages, gelatin offers poor mechanical properties, sensitive enzymatic degradation and high viscosity at room temperature which limits its application and encourages its use to develop biocomposites. Hydrophilic biomass-based cellulose nanofibrous (CNF) has been explored to use as suspension for biocomposite aerogels for the development of 3D porous structures with excellent mechanical properties, biocompatibility and slow enzymatic degradation. In this work, CNF biocomposite aerogels with various ratios of CNF:GEL) (90:10, 70:30 and 50:50) were prepared by freeze-drying technique, and their properties were investigated in terms of physicochemical, mechanical and biological characteristics. Epichlorohydrin (EPH) was used to investigate the effect of chemical crosslinking on the molecular interaction of CNF: GEL, and its effects on physicochemical, mechanical and biological properties of the biocomposite aerogels. Ultimately, chemical crosslinking helped to improve the mechanical resilience of the resulting aerogels. Amongst all the CNF-GEL composites, the crosslinked CNF: GEL (70:30) biocomposite was found to be favourable for cell attachment and viability. It possessed highly porous structure (porosity of ~93%) with pore sizes ranging from 16-110 µm, adequate mechanical properties (compression modulus of ~47 kPa) and optimal biocompatibility both in-vitro and in-vivo, as well as controlled enzymatic biodegradation, high water penetration, which could be considered a suitable option for wound healing application. In-vivo experiments showed improvement on inflammation and foreign giant body cell reaction for the crosslinked CNF: GEL (70:30) compared to the other samples. This could be due to the superior interaction of CNF with gelatin through chemical crosslinking, resulting in more optimal in-vivo improvement. In-vitro cell culture investigation on human dermal fibroblasts showed satisfactory 3D cell attachment over time. Overall, it has been observed that the developed CNF: GEL aerogel can be considered as a potential scaffold for soft tissue regeneration application.

Keywords: 3D scaffolds, aerogels, Biocomposites , tissue engineering

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Authors: Abdulrahman Sumayli

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Natural Zinc has many significant biological functions, including developments and sustainable of bones and wound healing. Metallic zinc has recently been explored as potential biomaterials that have preferable biodegradable, biocompatible, and mechanical properties. Pure metal zinc has a preferable physical and mechanical properties for biodegradable and biocompatible applications such as density and modulus of elasticity. The aim of the research is to make different Zn-based metallic alloys and test them effectively to be used as biocompatible and biodegradable materials in the field biomedical application. Microstructure study of the as-cast alloys will be examined using SEM (scanning electron microscope) followed by X-ray diffraction investigated so as to evaluate phase constitution of the designed alloys. After that, immersion test and electrochemical test will be applied to the designed alloys so as to study bio corrosion behaviour of the proposed alloys. Finally, in vitro cytocompatibility well conducted to study biocompatibility of the made alloys.

Keywords: Zn-based alloys, biodegradable and biocompatible materials, cytotoxicity test, neutron synchrotron imaging

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Authors: Pyi Phyo Maung

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In the study, the calculations of the permeability coefficient, values of the volume and porosity of a unit cell of a woven fabric before and after deformation based on the geometrical parameters are presented. Two types of carbon woven fabric structures were investigated: standard type, which integrated the filament, has a cross sectional shape of a cylinder and spread tow type, which has a rectangular cross sectional shape. The space antennas reflector, which distinctive feature is the presence of the surface of double curvature, is considered as the object of the research. Modeling of the kinetics of the process of impregnation of the reflector for the two types of carbon fabric’s unit cell structures was performed using software RAM-RTM. This work also investigated the influence of the grid angle between warp and welt of the unit cell on the duration of impregnation process. The results showed that decreasing the angle between warp and welt of the unit cell, the decreasing of the permeability values were occurred. Based on the results of calculation samples of the reflectors, their quality was determined. The comparisons of the theoretical and experimental results have been carried out. Comparison of the two textile structures (standard and spread tow) showed that the standard textiles with circular cross section were impregnated faster than spread tows, which have a rectangular cross section.

Keywords: vacuum assistant resin infusion, impregnation time, shear angle, reflector and modeling

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Authors: Bavneet Kaur Sidhu, Manoj Tiwari

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Global Developmental Delay (GDD) is a common pediatric condition. Etiologies of GDD might, however, differ in developing countries. In the last decade, sporadic families are being reported in various countries. As to the author’s best knowledge, many risk factors and their correlation with the prevalence of GDD have been studied but its statistical correlation has not been done. Thus we propose the present study by targeting the risk factor, prevalence and their statistical correlation with GDD. FMR1 gene was studied to confirm the disease and its penetrance. A complete questionnaire-based performance was designed for the statistical studies having a personal, past and present medical history along with their socio-economic status as well. Methods: We distributed the children’s age in 4 different age groups having 5-year intervals and applied structural equation modeling (SEM) techniques, Spearman’s rank correlation coefficient, Karl Pearson correlation coefficient, and chi-square test.Result: A total of 1100 families were enrolled for this study; among them, 330 were clinically and biologically confirmed (radiological studies) for the disease, 204 were males (61.8%), 126 were females (38.18%). We found that 27.87% were genetic and 72.12 were sporadic, out of 72.12 %, 43.277% cases from urban and 56.72% from the rural locality, the mothers' literacy rate was 32.12% and working women numbers were 41.21%. Conclusions: There is a significant association between mothers' age and GDD prevalence, which is also followed by mothers' literacy rate and mothers' occupation, whereas there was no association between fathers' age and GDD.

Keywords: global developmental delay, FMR1 gene, spearman’ rank correlation coefficient, structural equation modeling

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Authors: Buno Henriques, Rafaela Santos, Júlio Matias de Souza, Filipe Silva, Rubens Nascimento, Márcio Fredel

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Dental porcelain composites reinforced and toughened by 20 wt.% tetragonal zirconia (3Y-TZP) were processed by hot pressing at 1000°C. Two types of particles were tested: yttria-stabilized zirconia (ZrO2–3%Y2O3) agglomerates and pre-sintered yttria-stabilized zirconia (ZrO2–3%Y2O3) particles. The composites as well as the reinforcing particles were analyzed by the means of optical and Scanning Electron Microscopy (SEM), Energy Dispersion Spectroscopy (EDS) and X-Ray Diffraction (XRD). The mechanical properties were obtained by the transverse rupture strength test, Vickers indentations and fracture toughness. Wear tests were also performed on the composites and monolithic porcelain. The best mechanical and wear results were displayed by the porcelain reinforced with the pre-sintered ZrO2–3%Y2O3 particles.

Keywords: dental restoration, zirconia, porcelain, composites, strengthening, toughening, wear

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Authors: Bijit Kalita, R. Jayaganthan

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Additive manufacturing (AM) is a novel manufacturing method which provides more freedom in design, manufacturing near-net-shaped parts as per demand, lower cost of production, and expedition in delivery time to market. Among various metals, AM techniques, Laser Powder Bed Fusion (L-PBF) is the most prominent one that provides higher accuracy and powder proficiency in comparison to other methods. Particularly, 17-4 PH alloy is martensitic precipitation hardened (PH) stainless steel characterized by resistance to corrosion up to 300°C and tailorable strengthening by copper precipitates. Additively manufactured 17-4 PH stainless steel exhibited a dendritic/cellular solidification microstructure in the as-built condition. It is widely used as a structural material in marine environments, power plants, aerospace, and chemical industries. The excellent weldability of 17-4 PH stainless steel and its ability to be heat treated to improve mechanical properties make it a good material choice for L-PBF. In this study, the microstructures of martensitic stainless steels in the as-built state, as well as the effects of process parameters, building atmosphere, and heat treatments on the microstructures, are reviewed. Mechanical properties of fabricated parts are studied through micro-hardness and tensile tests. Tensile tests are carried out under different strain rates at room temperature. In addition, the effect of process parameters and heat treatment conditions on mechanical properties is critically reviewed. These studies revealed the performance of L-PBF fabricated 17–4 PH stainless-steel parts under cyclic loading, and the results indicated that fatigue properties were more sensitive to the defects generated by L-PBF (e.g., porosity, microcracks), leading to the low fracture strains and stresses under cyclic loading. Rapid melting, solidification, and re-melting of powders during the process and different combinations of processing parameters result in a complex thermal history and heterogeneous microstructure and are necessary to better control the microstructures and properties of L-PBF PH stainless steels through high-efficiency and low-cost heat treatments.

Keywords: 17–4 PH stainless steel, laser powder bed fusion, selective laser melting, microstructure, additive manufacturing

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Authors: Jae Seo Lee, Il Keun Kwon

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In the last decades, keratin-based on natural extracts has considerably increased interest as a skin tissue regeneration. However, most parts of keratin had a limitation to 3D scaffolds due to low biological affinity and general low mechanical properties. To create a 3D structure, a facile bioink was designed with a photocurable crosslinking stage system using natural polymer-based human keratin. Keratin-based bioink enables the crosslinking more quickly through two types of photo and ion crosslinking for module engineering assembly. Rheological results showed that keratin-based bioink with high concentration possessed superior mechanical rigidity for 3D bioprinting. Different 3D geometrically constructs were successfully fabricated with optimal bioprinting parameters through the 3D printer with X-Y-Z controlled UV laser system. The presented study has offered a distinct advantage for 3D printing of keratin-based hydrogel into 3D complex-shaped biomimetic constructs. Thus, keratin-based bioink opens up new avenues in bioprinting to directly substitute tissue or organs.

Keywords: human keratin, hydrogel, ion-crosslinking, 3D bioprinting

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Tesfaye Worku

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Human hair, chicken feathers, and hairs of other birds and animals are commonly described as waste products, and the currently available disposal methods, such as burying and burning these waste products, are contributing to environmental pollution. However, those waste products are used to develop fiber-reinforced textile composite material. In this research work, the composite was developed using human hair fiber and analysis of the mechanical and physical properties of the developed composite sample. A composite sample was made with different ratios of human hair and unsaturated polyester resin, and an analysis of the mechanical and physical properties of the developed composite sample was tested according to standards. The fabricated human hair fibers reinforced polymer matrix composite sample has given encouraging results in terms of high strength and rigidity for lightweight house ceiling board material.

Keywords: composite, human hair fiber, matrix, unsaturated polyester

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Authors: Lenka Markovičová, Viera Zatkalíková, Tomasz Garbacz

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The development of composite materials and the related design and manufacturing technologies is one of the most important advances in the history of materials. Composites are multifunctional materials having unprecedented mechanical and physical properties that can be tailored to meet the requirements of a particular application. Some composites also exhibit great resistance to high-temperature corrosion, oxidation, and wear. Polymers are widely used indoors and outdoors, therefore they are exposed to a chemical environment which may include atmospheric oxygen, acidic fumes, acidic rain, moisture heat and thermal shock, ultra-violet light, high energy radiation, etc. Different polymers are affected differently by these factors even though the amorphous polymers are more sensitive. Ageing is also important and it is defined as the process of deterioration of engineering materials resulting from the combined effects of atmospheric radiation, heat, oxygen, water, micro-organisms and other atmospheric factors.

Keywords: composites with glass fibers, mechanical properties, polyamides, UV degradation

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Authors: Jaya Prasad Vanam, Vinay Anurag P, Vidya Sravya N S, Kishore Babu Nagamothu

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Constrained Groove Pressing (CGP) is one of the severe plastic deformation technique (SPD) by which we can process Ultra Fine Grained (UFG)/plane metallic materials. This paper discusses the effects of CGP on Cu-Zn alloy specimen at room temperature. A comprehensive study is made on the structural and mechanical properties of Brass specimen before and after Constrained grooves Pressing. Entire process is simulated in AFDEX CAE Software. It is found that most of the properties are superior with respect to brass samples such as yield strength, ultimate tensile strength, hardness, strain rate, etc., and they are found to be better for the CGP processed specimen. The results are discussed with respective graphs.

Keywords: constrained groove pressing, AFDEX, ultra fine grained materials, severe plastic deformation technique

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Authors: Hyang Lim, Sungwon Choi

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Many previous studies in area of adolescents' depression have used a longitudinal design. The previous studies have found that the developmental trajectory of them is only one. But it needs to be examined whether the trajectory is applied to all adolescents. Some factors in their home and/or school have an effect on adolescents' depression and more likely to be specific groups. The present study was a longitudinal study aimed to identify the trajectories and to explore the predictors of adolescents' depression. The study used Korean Children and Youth Panel Survey (KCYPS) data. In this study, 2,351 second and third-year of middle school and first of high school students' data was analyzed by using semi-parametric group modeling (SGM). There were 5 trajectory groups for adolescents; low depressed stables, low depressed risers, moderately depressed decreases, moderately depressed stables, severe depressed decreases. The predictors of adolescents' depression were parental abuse, parental neglect, annual family income, parental academic background, friendship at school, and teacher-student relationship at school. All predictors had the significant difference across trajectory group profile for adolescents. The findings of the present study recommend to promote the socioeconomic status and to train social skill for the interpersonal relationship at the home and school. And the results suggest that the proper prevention programs for each group in the middle adolescents that target selected factors may be helpful in reducing the level of depression.

Keywords: adolescent, depression, KCYPS, school life, semi-parametric group-based modeling

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Authors: Sifriyani Sifriyani, I Nyoman Budiantara, Sri Haryatmi, Gunardi Gunardi

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East Java Province has a first rank as a province that has the most counties and cities in Indonesia and has the largest population. In 2015, the population reached 38.847.561 million, this figure showed a very high population growth. High population growth is feared to lead to increase the levels of unemployment. In this study, the researchers mapped and modeled the unemployment rate with 6 variables that were supposed to influence. Modeling was done by nonparametric geographically weighted regression methods with truncated spline approach. This method was chosen because spline method is a flexible method, these models tend to look for its own estimation. In this modeling, there were point knots, the point that showed the changes of data. The selection of the optimum point knots was done by selecting the most minimun value of Generalized Cross Validation (GCV). Based on the research, 6 variables were declared to affect the level of unemployment in eastern Java. They were the percentage of population that is educated above high school, the rate of economic growth, the population density, the investment ratio of total labor force, the regional minimum wage and the ratio of the number of big industry and medium scale industry from the work force. The nonparametric geographically weighted regression models with truncated spline approach had a coefficient of determination 98.95% and the value of MSE equal to 0.0047.

Keywords: East Java, nonparametric geographically weighted regression, spatial, spline approach, unemployed rate

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Authors: Ajith K. A. Gedara, Iva Chianella, Jose L. Endrino, Qi Zhang

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The olive seed is a by-product of the olive oil production industry. Biuret test and ferric chloride test revealed that water or alkali NaOH extractions of olive seed flour are rich in proteins and tannins. Both protein and tannins are well-known bio-based wood adhesives in the wood-based panel industry. In general, tannins-based adhesives show better mechanical and physical properties than protein wood adhesives. This paper explores different methods of extracting tannins from olive seed flour against the tannins yield and their applications as bio-based adhesives in wood-based panels. Once investigated, the physical and the mechanical properties of wood-based panels made using bio-adhesives based tannins extracted from olive seed flour revealed that the resulting products seemed to satisfy the Japanese Industrial Standards JIS A 5908:2015.

Keywords: bio-adhesives, olive seed flour, tannins, wood-based panels

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Authors: Mohammed S. Razali, Kamel Khimeche, Dahah Hichem, Ammar Boudjellal, Djamel E. Kaderi, Nourddine Ramdani

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The use of additive manufacturing technologies has revolutionized various aspects of our daily lives. In particular, 3D printing has greatly advanced biomedical applications. While fused filament fabrication (FFF) technologies have made it easy to produce or prototype various medical devices, it is crucial to minimize the risk of contamination. New materials with antibacterial properties, such as those containing compounded silver nanoparticles, have emerged on the market. In a previous study, we prepared a newly sintered seashell filler (SSh) from bio-based seashells found along the Mediterranean coast using a suitable heat treatment process. We then prepared a series of polylactic acid (PLA) and polybutylene succinate (PBS) biocomposites filled with these SSh particles using a melt mixing technique with a twin-screw extruder to use them as feedstock filaments for 3D printing. The study consisted of two parts: evaluating the antibacterial activity of newly prepared biocomposites made of PLA and PBS reinforced with a sintered seashell in the first part and experimental and modeling analysis of the non-isothermal crystallization kinetics of these biocomposites in the second part. In the first part, the bactericidal activity of the biocomposites against three different bacteria, including Gram-negative bacteria such as (E. coli and Pseudomonas aeruginosa), as well as Gram-positive bacteria such as (Staphylococcus aureus), was examined. The PLA-based biocomposite containing 20 wt.% of SSh particles exhibited an inhibition zone with radial diameters of 8mm and 6mm against E. coli and Pseudo. Au, respectively, while no bacterial activity was observed against Staphylococcus aureus. In the second part, the focus was on investigating the effect of the sintered seashell filler particles on the non-isothermal crystallization kinetics of PLA and PBS 3D-printing composite materials. The objective was to understand the impact of the filler particles on the crystallization mechanism of both PLA and PBS during the cooling process of a melt-extruded filament in (FFF) to manage the dimensional accuracy and mechanical properties of the final printed part. We conducted a non-isothermal melt crystallization kinetic study of a series of PLA-SS and PBS-SS composites using differential scanning calorimetry at various cooling rates. We analyzed the obtained kinetic data using different crystallization kinetic models such as modified Avrami, Ozawa, and Mo's methods. Dynamic mode describes the relative crystallinity as a function of temperature; it found that time half crystallinity (t1/2) of neat PLA decreased from 17 min to 7.3 min for PLA+5 SSh and the (t1/2) of virgin PBS was reduced from 3.5 min to 2.8 min for the composite containing 5wt.% of SSh. We found that the coated SS particles with stearic acid acted as nucleating agents and had a nucleation activity, as observed through polarized optical microscopy. Moreover, we evaluated the effective energy barrier of the non-isothermal crystallization process using the Iso conversional methods of Flynn-Wall-Ozawa (F-W-O) and Kissinger-Akahira-Sunose (K-A-S). The study provides significant insights into the crystallization behavior of PLA and PBS biocomposites.

Keywords: avrami model, bio-based reinforcement, dsc, gram-negative bacteria, gram-positive bacteria, isoconversional methods, non-isothermal crystallization kinetics, poly(butylene succinate), poly(lactic acid), antbactirial activity

Procedia PDF Downloads 62

Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: extra vehicular activity, biomechanics, inverse kinematics, human body modeling

Procedia PDF Downloads 326

Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

Procedia PDF Downloads 183

Authors: M. G. Shilina

Abstract:

The prospects for political and economic development of the Eurasian space are currently discussed at both governmental and expert levels. New concepts actively proposed by the Eurasian governments require the analysis and search for effective implementation options. In the paper, an attempt to identify effective solutions to the problems surrounding the current economic integration of the Eurasian states is given on the basis of an interdisciplinary, comprehensive, structured analysis. The phenomenon is considered through the prism of the international law, world economy and politics, combined with the study of existing intergovernmental practice. The modeling method was taken as the basis for the research and is supplemented by legal and empirical methods. The detailed multi-level model of practical construction the 'Great Eurasia' (the GE) concept is proposed, the option for building a phased interaction in Eurasia is given through the prism of construction by the Eurasian Economic Union (the EAEU) as the main tool. The Shanghai Cooperation Organization (the SCO) is seen as the most promising element of the model. The SCO is capable of streamlining the formation of the GE and determine the transformation of Eurasia into a common economic space. Effective development of the economic integration between Eurasian states on the framework of the SCO is optimal. The SCO+ could be used as a platform for integration-integration processes formation. The creation of stable financial ties could become the basis for the possible formation of an expanded transregional integration platform. The paper concludes that the implementation of the proposed model could entail a gradual economic rapprochement of Eurasia and beyond.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, the silk road economic belt

Procedia PDF Downloads 110

Authors: Sebastian Kohlstädt, Michael Vynnycky, Stephan Goeke, Jan Jäckel, Andreas Gebauer-Teichmann

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This paper summarizes the progress in the latest computational fluid dynamics research towards the modeling in of lost core viability in high-pressure die casting. High-pressure die casting is a process that is widely employed in the automotive and neighboring industries due to its advantages in casting quality and cost efficiency. The degrees of freedom are however somewhat limited as it has been so far difficult to use lost cores in the process. This is right now changing and the deployment of lost cores is considered a future growth potential for high-pressure die casting companies. The use of this technology itself is difficult though. The strength of the core material, as chiefly salt is used, is limited and experiments have shown that the cores will not hold under all circumstances and process designs. For this purpose, the publicly available CFD library foam-extend (OpenFOAM) is used, and two additional fluid models for incompressible and compressible two-phase flow are implemented as fluid solver models into the FSI library. For this purpose, the volume-of-fluid (VOF) methodology is used. The necessity for the fluid-structure interaction (FSI) approach is shown by a simple CFD model geometry. The model is benchmarked against analytical models and experimental data. Sufficient agreement is found with the analytical models and good agreement with the experimental data. An outlook on future developments concludes the paper.

Keywords: CFD, fluid-structure interaction, high-pressure die casting, multiphase flow

Procedia PDF Downloads 316

Authors: Irfan Anjum Manarvi, Zahid Ali kaimkhani

Abstract:

Predicting location of the fracture in human bones has been a keen area of research for the past few decades. A variety of tests for hardness, deformation, and strain field measurement have been conducted in the past; but considered insufficient due to various limitations. Researchers, therefore, have proposed further studies due to inaccuracies in measurement methods, testing machines, and experimental errors. Advancement and availability of hardware, measuring instrumentation, and testing machines can now provide remedies to these limitations. The human foot is a critical part of the body exposed to various forces throughout its life. A number of products are developed for using it for protection and care, which many times do not provide sufficient protection and may itself become a source of stress due to non-consideration of the delicacy of bones in the feet. A continuous strain or overloading on feet may occur resulting to discomfort and even fracture. Mechanical properties of Tarsals, Metatarsals, and phalanges are, therefore, the primary area of consideration for all such design applications. Hardness is one of the mechanical properties which are considered very important to establish the mechanical resistance behavior of a material against applied loads. Past researchers have worked in the areas of investigating mechanical properties of these bones. However, their results were based on a limited number of experiments and taking average values of hardness due to either limitation of samples or testing instruments. Therefore, they proposed further studies in this area. The present research has been carried out to develop a hardness map of the human foot by measuring micro hardness at various locations of these bones. Results are compiled in the form of distance from a reference point on a bone and the hardness values for each surface. The number of test results is far more than previous studies and are spread over a typical bone to give a complete hardness map of these bones. These results could also be used to establish other properties such as stress and strain distribution in the bones. Also, industrial engineers could use it for design and development of various accessories for human feet health care and comfort and further research in the same areas.

Keywords: tarsals, metatarsals, phalanges, hardness testing, biomechanics of human foot

Procedia PDF Downloads 411

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

Abstract:

This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

Procedia PDF Downloads 14