Search results for: excess thermodynamic parameters

Authors: M. Mydlárová Blaščáková, J. Poráčová, Z. Tomková, Ľ. Blaščáková, M. Nagy, M. Konečná, E. Petrejčíková, Z. Gogaľová, V. Sedlák, J. Mydlár, M. Zahatňanská, K. Hricová

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Osteoporosis is a multifactorial disease that results in reduced quality of life, causes decreased bone strength, and changes in their microarchitecture. Mostly postmenopausal women are at risk. In our study, we measured anthropometric parameters of postmenopausal women (104 women of control group – CG and 105 women of osteoporotic group - OG) and determined TSH hormone levels and PTH as well as mineral elements - Ca, P, Mg and enzyme alkaline phosphatase. Through the correlation analysis in CG, we have found association based on age and BMI, P and Ca, as well as Mg and Ca; in OG we determined interdependence based on an association of age and BMI, age and Ca. Using the Student's t test, we found significantly important differences in biochemical parameters of Mg (p ˂ 0,001) and TSH (p ˂ 0,05) between CG and OG.

Keywords: factors, bone mass density, Central Europe, biomarkers

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: M. H. A. D. de Silva, R. P. Hewawasam, M. A. G. Iresha

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Macrosomia is common in infants born to not only women diagnosed with gestational diabetes mellitus but also non-diabetic obese women. Maternal Body Mass Index (BMI) correlates with the incidence of large for gestational age infants. Obesity has reached epidemic levels in modern societies. During the past two decades, obesity in children and adolescents has risen significantly in Asian populations including Sri Lanka. There is increasing evidence to believe that infants who are born large for gestational age are more likely to be obese in childhood and adolescence and are at risk of cardiovascular and metabolic complications later in life. It is also established that Asians have lower skeletal muscle mass, low bone mineral content and excess body fat for a given BMI indicating a genetic predisposition in the occurrence of obesity. The objective of this study is to determine the effect of maternal weight, weight gain during pregnancy, c-peptide and insulin concentrations in the cord blood on the birth of appropriate for and large for gestational age infants in a tertiary care center in Southern Sri Lanka. Umbilical cord blood was collected from 90 newborns (Male 40, Female 50; gestational age 35-42 weeks) after double clamping the umbilical cord before separation of the placenta and the concentration of insulin and C-peptide were measured by ELISA technique. Anthropometric parameters of the newborn such as birth weight, length, ponderal index, occipital frontal, chest, hip and calf circumferences were measured, and characteristics of the mother were collected. The relationship between insulin, C-peptide and anthropometrics were assessed by Spearman correlation. The multiple logistic regression analysis examined influences of maternal weight, weight gain during pregnancy, C-peptide and insulin concentrations in cord blood as covariates on the birth of large for gestational age infants. A significant difference (P<0.001) was observed between the insulin levels of infants born large for gestational age (18.73 ± 0.52 µlU/ml) and appropriate for gestational age (13.08 ± 0.56 µlU/ml). Consistently, A significant decrease in concentration (41.68%, P<0.001) was observed between C-peptide levels of infants born large for gestational age and appropriate for gestational age. Cord blood insulin and C-peptide levels had a significant correlation with birth weight (r=0.35, P<0.05) of the newborn at delivery. Maternal weight and BMI which are indicators of maternal nutrition were proven to be directly correlated with birth weight and length. To our knowledge, this relationship was investigated for the first time in a Sri Lankan setting and was also evident in our results. This study confirmed the fact that insulin and C-peptide play a major role in regulating fetal growth. According to the results obtained in this study, we can suggest that the increased BMI of the mother has a direct influence on increased maternal insulin secretion, which may subsequently affect cord insulin and C-peptide levels and also birth weight of the infant.

Keywords: C-peptide, insulin, large for gestational age, maternal weight

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Authors: V. Pourmostaghimi, M. Zadshakoyan

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Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Muhammad Bilal Ameen, M. Zubair Akbar Qureshi

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The current investigation of two-dimensional hybrid nanofluid flows with two coaxial parallel disks has been presented. Consider the hybrid nanofluid has been taken as steady-state. Consider the coaxial disks that have been porous. Consider the heat equation to examine joule heating and viscous dissipation effects. Nonlinear partial differential equations have been solved numerically. For shear stress and heat transfer, results are tabulated. Hybrid nanoparticles and Eckert numbers are increasing for heat transfer. Entropy generation is expanded with radiation parameters Eckert, Reynold, Prandtl, and Peclet numbers. A set of ordinary differential equations is obtained to utilize the capable transformation variables. The numerical solution of the continuity, momentum, energy, and entropy generation equations is obtaining using the command bvp4c of Matlab as a solver. To explore the impact of main parameters like suction/infusion, Prandtl, Reynold, Eckert, Peclet number, and volume fraction parameters, various graphs have been plotted and examined. It is concluded that a convectional nanofluid is highly compared by entropy generation with the boundary layer of hybrid nanofluid.

Keywords: entropy generation, hybrid nano fluid, heat transfer, porous disks

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Authors: Yasser El-Henawy, M. Abd El-Kader, Gamal H. Moustafa

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A theoretical study of a humidification dehumidification solar desalination unit has been carried out to increase understanding the effect of weather conditions on the unit productivity. A humidification-dehumidification (HD) solar desalination unit has been designed to provide fresh water for population in remote arid areas. It consists of solar water collector and air collector; to provide the hot water and air to the desalination chamber. The desalination chamber is divided into humidification and dehumidification towers. The circulation of air between the two towers is maintained by the forced convection. A mathematical model has been formulated, in which the thermodynamic relations were used to study the flow, heat and mass transfer inside the humidifier and dehumidifier. The present technique is performed in order to increase the unit performance. Heat and mass balance has been done and a set of governing equations has been solved using the finite difference technique. The unit productivity has been calculated along the working day during the summer and winter sessions and has compared with the available experimental results. The average accumulative productivity of the system in winter has been ranged between 2.5 to 4 kg/m2.day, while the average summer productivity has been found between 8 to 12 kg/m2 day.

Keywords: solar desalination, solar collector, humidification and dehumidification, simulation, finite difference, water productivity

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

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Authors: Shourav Ahmed, M. Gulam Kibria, Kais Zaman

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Control charts graphically verify variation in quality parameters. Attribute type control charts deal with quality parameters that can only hold two states, e.g., good or bad, yes or no, etc. At present, p-control chart is most commonly used to deal with attribute type data. In construction of p-control chart using binomial distribution, the value of proportion non-conforming must be known or estimated from limited sample information. As the probability distribution of fraction non-conforming (p) is considered in hyperbinomial distribution unlike a constant value in case of binomial distribution, it reduces the risk of false detection. In this study, a statistical control chart is proposed based on hyperbinomial distribution when prior estimate of proportion non-conforming is unavailable and is estimated from limited sample information. We developed the control limits of the proposed modified p-chart using the mean and variance of hyperbinomial distribution. The proposed modified p-chart can also utilize additional sample information when they are available. The study also validates the use of modified p-chart by comparing with the result obtained using cumulative distribution function of hyperbinomial distribution. The study clearly indicates that the use of hyperbinomial distribution in construction of p-control chart yields much accurate estimate of quality parameters than using binomial distribution.

Keywords: binomial distribution, control charts, cumulative distribution function, hyper binomial distribution

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Authors: Seyedeh Belin Tavakoly Sany, Rosli Hashim, Majid Rezayi, Aishah Salleh

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The primary objectives of this study were to investigate the distribution and composition of the macrobenthic community and their response to environmental parameters in the North Port, west coastal waters of Malaysia. A total of 25 species were identified, including 13 bivalvia, 4 gastropoda, and 3 crustacea. The other taxa were less diversified. There were no temporal changes in the macrobenthic community composition, but significant effects (p < 0.05) on the benthic community composition were found on a spatial scale. The correlation analyses and similarity tests were in good agreement, confirming the significant response of macrobenthic community composition to variations of environmental parameters.

Keywords: distribution, macrobenthic community, diversity, North Port, Malaysia

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Authors: M. Bahgat, F. M. Awan, H. A. Hanafy

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The conventional ceramic route was utilized to prepare a hard magnetic powder (M-type strontium ferrite, SrFe12O19). The stoichiometric mixture of iron oxide and strontium carbonate were calcined at 1000°C and then fired at various temperatures. The influence of various reaction parameters such as mixing ratio, calcination temperature, firing temperature and firing time on the magnetic behaviors of the synthesized magnetic powder were investigated.The magnetic properties including Coercivity (Hc), Magnetic saturation (Ms), and Magnetic remnance (Mr) were measured by vibrating sample magnetometer. Morphologically the produced magnetic powder has a dense hexagonal grain shape structure.

Keywords: hard magnetic materials, ceramic route, strontium ferrite, magnetic properties

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Authors: Asna Anchalan, Anjana Bhagyanathan

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Urban green space plays an important role in providing health (physical and mental well-being), economic, and environmental benefits for urban residents and neighborhoods. Ensuring equitable distribution of urban green space is vital to ensure equal access to these benefits. This study is developing a methodology for assessing spatial equity of urban green spaces in the Indian context. Through a systematic literature review, the research trends, parameters, data, and tools being used are identified. After 2020, the research in this domain is increasing rapidly, where COVID-19 acted as a catalyst. Indian documents use various terminologies, definitions, and classifications of urban green spaces. The terminology, definition, and classification for this study are done after reviewing several Indian documents, master plans, and research papers. Parameters identified for assessing spatial equity are availability, proximity, accessibility, and socio-economic disparity. Criteria for evaluating each parameter were identified from diverse research papers. There is a research gap identified as a comprehensive approach encompassing all four parameters. The outcome of this study led to the development of a methodology that addresses the gaps, providing a practical tool applicable across diverse Indian cities.

Keywords: urban green space, spatial equity, accessibility, proximity, methodology

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Authors: Amin Chegenizadeh, Mahdi Keramatikerman, Hamid Nikraz

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Pavement engineering plays a significant role to develop cost effective and efficient highway and road networks. In general, pavement regarding structure is categorized in two core group namely flexible and rigid pavements. There are various benefits in application of rigid pavement. For instance, they have a longer life and lower maintenance costs in compare with the flexible pavement. In rigid pavement designs, temperature and thickness are two effective parameters that could widely affect the total cost of the project. In this study, a numerical modeling using Kenpave-Kenslab was performed to investigate the effect of these two important parameters in the rigid pavement.   

Keywords: rigid pavement, Kenpave, Kenslab, thickness, temperature

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Authors: Vhuhwavho Gadisi, Rebecca Alowo, German Nkhonjera

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It has been noted that technical programming for handling groundwater resources is not accessible. The lack of these systems hinders groundwater management processes necessary for decision-making through monitoring and evaluation regarding the Jukskei River of the Crocodile River (West) Basin in Johannesburg, South Africa. Several challenges have been identified in South Africa's Jukskei Catchment concerning groundwater management. Some of those challenges will include the following: Gaps in data records; there is a need for training and equipping of monitoring staff; formal accreditation of monitoring capacities and equipment; there is no access to regulation terms (e.g., meters). Taking into consideration necessities and human requirements as per typical densities in various regions of South Africa, there is a need to construct several groundwater level monitoring stations in a particular segment; the available raw data on groundwater level should be converted into consumable products for example, short reports on delicate areas (e.g., Dolomite compartments, wetlands, aquifers, and sole source) and considering the increasing civil unrest there has been vandalism and theft of groundwater monitoring infrastructure. GIS was employed at the catchment level to plot the relationship between those identified groundwater parameters in the catchment area and the identified borehole. GIS-based maps were designed for groundwater monitoring to be pretested on one borehole in the Jukskei catchment. This data will be used to establish changes in the borehole compared to changes in the catchment area according to identified parameters.

Keywords: GIS, monitoring, Jukskei, catchment

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Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying is one of the most critical unit operations for prolonging the shelf-life of food grains in order to ensure global food security. Photovoltaic integrated solar dryers can be a sustainable solution for replacing energy intensive thermal dryers as it is capable of drying in off-sunshine hours and provide better control over drying conditions. But, performance and reliability of PV based solar dryers depend hugely on climatic conditions thereby, drastically affecting process parameters. Therefore, to ensure quality and prolonged shelf-life of paddy, optimization of process parameters for solar dryers is critical. Proper moisture distribution within the grains is most detrimental factor to enhance the shelf-life of paddy therefore; modeling of mass transport can help in providing a better insight of moisture migration. Hence, present work aims at optimizing the process parameters and to develop a 3D finite element model (FEM) for predicting moisture profile in paddy during solar drying. Optimization of process parameters (power level, air velocity and moisture content) was done using box Behnken model in Design expert software. Furthermore, COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Optimized model for drying paddy was found to be 700W, 2.75 m/s and 13% wb with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Furthermore, 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product to achieve global food and energy security

Keywords: finite element modeling, hybrid solar drying, mass transport, paddy, process optimization

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Authors: Takashi Kaminagayoshi, Shigeyuki Haruyama

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To improve the manufacturing efficiency of biologics, such as antibody drugs, a quality engineering framework was designed. Within this framework, critical steps and parameters in the manufacturing process were studied. Identification of these critical steps and critical parameters allows a deeper understanding of manufacturing capabilities, and suggests to process development department process control standards based on actual manufacturing capabilities as part of a PDCA (plan-do-check-act) cycle. This cycle can be applied to each manufacturing process so that it can be standardized, reducing the time needed to establish each new process.

Keywords: antibody drugs, biologics, manufacturing efficiency, PDCA cycle, quality engineering

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Authors: Ildar Akhmadullin, Mayank Tyagi

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The subject of this paper is the design analysis of a single well power production unit from low enthalpy geothermal resources. A complexity of the project is defined by a low temperature heat source that usually makes such projects economically disadvantageous using the conventional binary power plant approach. A proposed new compact design is numerically analyzed. This paper describes a thermodynamic analysis, a working fluid choice, downhole heat exchanger (DHE) and turbine calculation results. The unit is able to produce 321 kW of electric power from a low enthalpy underground heat source utilizing n-Pentane as a working fluid. A geo-pressured reservoir located in Vermilion Parish, Louisiana, USA is selected as a prototype for the field application. With a brine temperature of 126℃, the optimal length of DHE is determined as 304.8 m (1000ft). All units (pipes, turbine, and pumps) are chosen from commercially available parts to bring this project closer to the industry requirements. Numerical calculations are based on petroleum industry standards. The project is sponsored by the Department of Energy of the US.

Keywords: downhole heat exchangers, geothermal power generation, organic rankine cycle, refrigerants, working fluids

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Authors: D.Rached, M.Rabah

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First principles calculations are carried out to investigate the structural, electronic, and elastic properties of the utraincompressible materials, namely, noble metal carbide of Rhenium carbide (ReC) in four phases, the rocksalt (NaCl-B1), zinc blende (ZB-B2), the tungsten carbide(Bh) (WC), and the nickel arsenide (NiAs-B8).The ground state properties such as the equilibrium lattice constant, elastic constants, the bulk modulus its pressure derivate, and the hardness of ReC in these phases are systematically predicted by calculations from first–principles. The corresponding calculated bulk modulus is comparable with that of diamond, especially for the B8 –type rhenium carbide (ReC), the incompressibility along the c axis is demonstrated to exceed the linear incompressibility of diamond. Our calculations confirm in the nickel arsenide (B8) structure the ReC is found to be stable with a large bulk modulus B=440 GPa and the tungsten carbide (WC) structure becomes the most more favourable with to respect B3 and B1 structures, which ReC- WC is meta-stable. Furthermore, the highest bulk modulus values in the zinc blende (B3), rock salt (B1), tungsten carbide (WC), and the nickel arsenide (B8) structures (294GPa, 401GPa, 415GPa and 447 GPa, respectively) indicates that ReC is a hard material, and is superhard compound H(B8)= 36 GPa compared with the H(diamond)=96 GPa and H(c BN)=63.10 GPa.

Keywords: DFT, FP-LMTO, mechanical properties, elasticity, high pressure, thermodynamic properties, hard material

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Authors: Mustafa Kemal Bilici, Memduh Kurtulmuş, İlyas Kartal, Ahmet İrfan Yükler

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Friction stir welding is a solid-state joining process that has gained acceptable progress in recent years. This method which was first used for welding of aluminum and its alloys is now employed for welding of other materials such as polymers and composites. The aim of the present work is to investigate the mechanical properties of butt joints produced by friction stir welding (FSW) in high density polyethylene sheets of 4 mm thickness. The effects of critical welding parameters and tool design have affected on mechanical properties, weld surface and macrostructure of friction stir welded polyethylene. Experiments were performed at tool rotational speeds of 600, 900, 1200 and 1500 r/min and traverse speeds of 30, 45 and 60 mm/min, tool diameters (d) of 4, 5, 6 mm and tool shoulder diameters (D) 20, 25, 30 mm. A strength value of 80 % of the base material was achieved at the isolated optimum welding condition. According to the tool design, the welding parameters and the mechanical properties changed to a great extent. The highest tensile strength was achieved at low feed rates, high tool rotation speeds and shoulder diameters/pin diameters ratio.

Keywords: friction stir welding, mechanical properties, polyethylene, high density polyethylene, tool design

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Authors: Sanjib Kr Pal, S. Bhattacharyya

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Mixed convection of Cu-water nanofluid in an enclosure with thick wavy bottom wall has been investigated numerically. A co-ordinate transformation method is used to transform the computational domain into an orthogonal co-ordinate system. The governing equations in the computational domain are solved through a pressure correction based iterative algorithm. The fluid flow and heat transfer characteristics are analyzed for a wide range of Richardson number (0.1 ≤ Ri ≤ 5), nanoparticle volume concentration (0.0 ≤ ϕ ≤ 0.2), amplitude (0.0 ≤ α ≤ 0.1) of the wavy thick- bottom wall and the wave number (ω) at a fixed Reynolds number. Obtained results showed that heat transfer rate increases remarkably by adding the nanoparticles. Heat transfer rate is dependent on the wavy wall amplitude and wave number and decreases with increasing Richardson number for fixed amplitude and wave number. The Bejan number and the entropy generation are determined to analyze the thermodynamic optimization of the mixed convection.

Keywords: conjugate heat transfer, mixed convection, nano fluid, wall waviness

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Authors: Shoumodip Roy, Ankit Singhania, Santanu Mallick, Abhiram Jha, M. K. Agarwal, R. V. Ramna, Uttam Singh

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The quality of hot metal at any blast furnace is judged by the silicon content in it. Lower hot metal silicon not only enhances process efficiency at steel melting shops but also reduces hot metal costs. The Hot metal produced at G-Blast furnace Tata Steel Jamshedpur has a significantly higher Si content than Benchmark Blast furnaces. The higher content of hot metal Si is mainly due to inferior raw material quality than those used in benchmark blast furnaces. With minimum control over raw material quality, the only option left to control hot metal Si is via optimizing the furnace parameters. Therefore, in order to identify the levers to reduce hot metal Si, Data mining was carried out, and multiple regression models were developed. The statistical analysis revealed that Slag B3{(CaO+MgO)/SiO2}, Slag Alumina and Hot metal temperature are key controllable parameters affecting hot metal silicon. Contour Plots were used to determine the optimum range of levels identified through statistical analysis. A trial plan was formulated to operate relevant parameters, at G blast furnace, in the identified range to reduce hot metal silicon. This paper details out the process followed and subsequent reduction in hot metal silicon by 15% at G blast furnace.

Keywords: blast furnace, optimization, silicon, statistical tools

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Authors: S. Fazi, B. Behdani

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The inland transportation of maritime containers entails the use of different modalities whose capacity is typically booked in advance. Containers may miss their scheduled departure time at a terminal for several reasons, such as delays, change of transport modes, multiple bookings pending. In those cases, it may be difficult for transport service providers to find last minute containers to fill the vacant capacity. Similarly to other industries, overbooking could potentially limit these drawbacks at the cost of a lower service level in case of actual excess of capacity in overbooked rides. However, the presence of multiple modalities may provide the required flexibility in rescheduling and limit the dissatisfaction of the shippers in case of containers in overbooking. This flexibility is known with the term 'synchromodality'. In this paper, we evaluate via discrete event simulation the application of overbooking. Results show that in certain conditions overbooking can significantly increase profit and utilization of high-capacity means of transport, such as barges and trains. On the other hand, in case of high penalty costs and limited no-show, overbooking may lead to an excessive use of expensive trucks.

Keywords: discrete event simulation, flexibility, inland shipping, multimodality, overbooking

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Authors: Junaid Bin Aamir, Ma Fanhua

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Methanol is one of the most suitable alternative fuels for replacing gasoline in present and future spark-ignited engines. However, for pure methanol engines, cold start problems and misfires are observed under certain operating conditions. Hydrogen provides a solution for such problems. This paper experimentally investigated the effect of hydrogen on the performance of a pure methanol SI-engine at city driving conditions (1500 rpm speed and 1.18 excess air ratio). Hydrogen was used as a part of methanol reformed syngas (67% hydrogen by volume). 4% by mass of the total methanol converted to hydrogen and other constituent gases, was used in each cycle. Port fuel injection was used to inject methanol and hydrogen-rich syngas into the 4-cylinder engine. The results indicated an increase in brake thermal efficiency up to 5% with the addition of hydrogen, a decrease in brake specific fuel consumption up to 200 g/kWh, and a decrease in exhaust gas temperature by 100°C for all mean effective pressures. Hydrogen addition also decreased harmful exhaust emissions significantly. There was a reduction in THC emissions up to 95% and CO emissions up to 50%. NOx emissions were slightly increased (up to 15%), but they can be reduced to zero by lean burn strategy.

Keywords: alternative fuels, hydrogen, methanol, performance, spark ignition engines

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Authors: Ali Ates, Sadık Ata, Kevser Dincer

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In this study, performance of the driver seat‘s localized cooling and heating in a standard car air conditioning system was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Climate function at automobile is an important variable for thermal comfort. In the experimental study localized heating and cooling performances have been examined with the aid of a mechanism established to a vehicle. The equipment’s used in the experimental setup/mechanism have been provided and assembled. During the measurement, the status of the performance level has been determined. Input parameters revolutions per minute and time; output parameters car seat cooling temperature, car back cooling temperature, car seat heating temperature, car back heating temperature were described by RBMTF if-the rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF could be successfully used in standard car air conditioning system.

Keywords: air conditioning system, cooling-heating, RMBTF modelling, car seat

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Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

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Authors: Malarvizhi, Venkatesan

Abstract:

This paper summarizes about the design and optimization of solar powered unmanned aerial vehicle. The purpose of this research is to increase the range and endurance. It can be used for environmental research, aerial photography, search and rescue mission and surveillance in other planets. The ultimate aim of this research is to design and analyze the solar powered plane in order to detect lift, drag and other parameters by using cfd analysis. Similarly the numerical investigation has been done to compare the results of earth’s atmosphere to the mars atmosphere. This is the approach made to check whether the solar powered plane is possible to glide in the planet mars by using renewable energy (i.e., solar energy).

Keywords: optimization, range, endurance, surveillance, lift and drag parameters

Procedia PDF Downloads 457

Authors: Mehmet Savsar

Abstract:

This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

Procedia PDF Downloads 481

Authors: Mokhtar Nikgoo

Abstract:

Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

Procedia PDF Downloads 91

Authors: Mamidi Ramakrishna Rao

Abstract:

Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

Procedia PDF Downloads 248

Authors: İkbal Eski

Abstract:

This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

Procedia PDF Downloads 387