New Technologies for Modeling of Gas Turbine Cooled Blades

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Numerical Modeling of Direct Shear Tests on Sandy Clay

Investigation of sandy clay behavior is important since urban development demands mean that sandy clay areas are increasingly encountered, especially for transportation infrastructures. This paper presents the results of the finite element analysis of the direct shear test (under three vertical loading 44, 96 and 192 kPa) and discusses the effects of different parameters such as cohesion, friction angle and Young's modulus on the shear strength of sandy clay. The numerical model was calibrated against the experimental results of large-scale direct shear tests. The results have shown that the shear strength was increased with increase in friction angle and cohesion. However, the shear strength was not influenced by raising the friction angle at normal stress of 44 kPa. Also, the effect of different young's modulus factors on stress-strain curve was investigated.

Evaluation of Eating Habits among Portuguese University Students: A Preliminary Study

Portuguese diet has been gradually diverging from the basic principles of healthy eating, leading to an unbalanced dietary pattern which, associated with increasing sedentary lifestyle, has a negative impact on public health. The main objective of this work was to characterize the dietary habits of university students in Viseu, Portugal. The study consisted of a sample of 80 university students, aged between 18 and 28 years. Anthropometric data (weight (kg) and height (m)) were collected and Body Mass Index (BMI) was calculated. The dietary habits were assessed through a three-day food record and the software Medpoint was used to convert food into energy and nutrients. The results showed that students present a normal body mass index. Female university students made a higher number of daily meals than male students, and these last skipped breakfast more frequently. The values of average daily intake of energy, macronutrients and calcium were higher in males. The food pattern was characterized by a predominant consumption of meat, cereal, fats and sugar. Dietary intake of dairy products, fruits, vegetables and legumes does not meet the recommendations, revealing inadequate food habits such as hypoglycemic, hyperprotein and hyperlipidemic diet. Our findings suggest that preventive interventions should be focus in promoting healthy eating habits and physical activity in adulthood.

Viability of Bradyrhizobium japanicum on Soybean Seeds Enhanced by Magnetite Nanoparticles during Desiccation

The aim of this study was to investigate whether magnetite nanoparticles affect the viability of Bradyrhizobium japanicum cells residing on the surface of soybean seeds during desiccation. Different concentrations of nanoparticles suspended in liquid medium, mixed with and adhering to Bradyrhizobium japanicum, were investigated at two temperatures, using both soybean seeds and glass beads as surrogates. Statistical design was a complete randomized block (CRB) in a factorial 6×2×2×6 experimental arrangement with four replications. The most important variable was the viability of Bradyrhizobium on the surface of the seeds. The nanoparticles increased Bradyrhizobium viability and inoculated seeds stored at low temperature had greater viability when nanoparticles had been added. At the optimum nanoparticle concentration, 50% bacterium viability on the seeds was retained after 5 days at 4ºC. Possible explanations for the observed effects are proposed.

Preparation and Bioevaluation of DOTA-Cyclic RGD Peptide Dimer Labeled with 68Ga

Radiolabeled cyclic RGD peptides targeting integrin αvβ3 are reported as promising agents for the early diagnosis of metastatic tumors. With an aim to improve tumor uptake and retention of the peptide, cyclic RGD peptide dimer E[c (RGDfK)] 2 (E = Glutamic acid, f = phenyl alanine, K = lysine) coupled to the bifunctional chelator DOTA was custom synthesized and radiolabelled with 68Ga. Radiolabelling of cyclic RGD peptide dimer with 68Ga was carried out using HEPES buffer and biological evaluation of the complex was done in nude mice bearing HT29 tumors.

Japan’s Policy towards the Countries of Central Asia

This article analyses the peculiarities of Japan’s policy toward the countries of Central Asia. The increasing role of Central Asia in the system of international relations engendered an objective need for understanding of the policy of leading states, including Japan, in the region in the twenty-first century. The purpose of the study is to investigate the peculiarities of the formation and development of Japan policy in Central Asia and to identify the problems and prospects of Japan’s policy toward the countries of the region on the basis of experts’ opinions. In this article, the method of analysis of the situation and a systematic method were used. Prognostic methods, the collective expert assessment and scenarios were used in the study to determine the prospects of Japan’s policy toward the countries of Central Asia.

An Ontology for Spatial Relevant Objects in a Location-aware System: Case Study: A Tourist Guide System

Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Nonlinear Thermal Expansion Model for SiC/Al

The thermal expansion behaviour of silicon carbide (SCS-2) fibre reinforced 6061 aluminium matrix composite subjected to the influenced thermal mechanical cycling (TMC) process were investigated. The thermal stress has important effect on the longitudinal thermal expansion coefficient of the composites. The present paper used experimental data of the thermal expansion behaviour of a SiC/Al composite for temperatures up to 370°C, in which their data was used for carrying out modelling of theoretical predictions.

Development of a Clustered Network based on Unique Hop ID

In this paper, Land Marks for Unique Addressing( LMUA) algorithm is develped to generate unique ID for each and every node which leads to the formation of overlapping/Non overlapping clusters based on unique ID. To overcome the draw back of the developed LMUA algorithm, the concept of clustering is introduced. Based on the clustering concept a Land Marks for Unique Addressing and Clustering(LMUAC) Algorithm is developed to construct strictly non-overlapping clusters and classify those nodes in to Cluster Heads, Member Nodes, Gate way nodes and generating the Hierarchical code for the cluster heads to operate in the level one hierarchy for wireless communication switching. The expansion of the existing network can be performed or not without modifying the cost of adding the clusterhead is shown. The developed algorithm shows one way of efficiently constructing the

Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Model Reduction of Linear Systems by Conventional and Evolutionary Techniques

Reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM), using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Mihailov stability criterion and continued fraction expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. In the evolutionary technique method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Hole Configuration Effect on Turbine Blade Cooling

In this paper a numerical technique is used to predict the metal temperature of a gas turbine vane. The Rising combustor exit temperatures in gas turbine engines necessitate active cooling for the downstream turbine section to avoid thermal failure. This study is performed the solution of external flow, internal convection, and conduction within the metal vane. Also the trade-off between the cooling performances in four different hole shapes and configurations is performed. At first one of the commonly used cooling hole geometry is investigated; cylindrical holes and then two other configurations are simulated. The average temperature magnitude in mid-plan section of each configuration is obtained and finally the lower temperature value is selected such as best arrangement.

Fault Detection of Drinking Water Treatment Process Using PCA and Hotelling's T2 Chart

This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.

Heart Rate Variability in Responders and Non- Responders to Live-Moderate, Train-Low Altitude Training

The aim of this study was to compare the effects of an altitude training camp on heart rate variability and performance in elite triathletes. Ten athletes completed 20 days of live-high, train-low training at 1650m. Athletes underwent pre and post 800-m swim time trials at sea-level, and two heart rate variability tests at 1650m on the first and last day of the training camp. Based on their time trial results, athletes were divided into responders and non-responders. Relative to the non-responders, the responders sympathetic-toparasympathetic ratio decreased substantially after 20 days of altitude training (-0.68 ± 1.08 and -1.2 ± 0.96, mean ± 90% confidence interval for supine and standing respectively). In addition, sympathetic activity while standing was also substantially lower post-altitude in the responders compared to the non-responders (-1869 ± 4764 ms2). Results indicate that responders demonstrated a change to more vagal predominance compared to non-responders.

Fuzzy Logic Based Determination of Battery Charging Efficiency Applied to Hybrid Power System

Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.

Development of a Project Selection Method on Information System Using ANP and Fuzzy Logic

Project selection problems on management information system (MIS) are often considered a multi-criteria decision-making (MCDM) for a solving method. These problems contain two aspects, such as interdependencies among criteria and candidate projects and qualitative and quantitative factors of projects. However, most existing methods reported in literature consider these aspects separately even though these two aspects are simultaneously incorporated. For this reason, we proposed a hybrid method using analytic network process (ANP) and fuzzy logic in order to represent both aspects. We then propose a goal programming model to conduct an optimization for the project selection problems interpreted by a hybrid concept. Finally, a numerical example is conducted as verification purposes.

Fuzzy Multi-Criteria Framework for Supporting Biofuels Policy Making

In this paper, a fuzzy algorithm and a fuzzy multicriteria decision framework are developed and used for a practical question of optimizing biofuels policy making. The methodological framework shows how to incorporate fuzzy set theory in a decision process of finding a sustainable biofuels policy among several policy options. Fuzzy set theory is used here as a tool to deal with uncertainties of decision environment, vagueness and ambiguities of policy objectives, subjectivities of human assessments and imprecise and incomplete information about the evaluated policy instruments.

Preparation and Investigation of Photocatalytic Properties of ZnO Nanocrystals: Effect of Operational Parameters and Kinetic Study

ZnO nanocrystals with mean diameter size 14 nm have been prepared by precipitation method, and examined as photocatalyst for the UV-induced degradation of insecticide diazinon as deputy of organic pollutant in aqueous solution. The effects of various parameters, such as illumination time, the amount of photocatalyst, initial pH values and initial concentration of insecticide on the photocatalytic degradation diazinon were investigated to find desired conditions. In this case, the desired parameters were also tested for the treatment of real water containing the insecticide. Photodegradation efficiency of diazinon was compared between commercial and prepared ZnO nanocrystals. The results indicated that UV/ZnO process applying prepared nanocrystalline ZnO offered electrical energy efficiency and quantum yield better than commercial ZnO. The present study, on the base of Langmuir-Hinshelwood mechanism, illustrated a pseudo first-order kinetic model with rate constant of surface reaction equal to 0.209 mg l-1 min-1 and adsorption equilibrium constant of 0.124 l mg-1.

A Universal Model for Content-Based Image Retrieval

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

RBF Based Face Recognition and Expression Analysis

Facial recognition and expression analysis is rapidly becoming an area of intense interest in computer science and humancomputer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper skin and non-skin pixels were separated. Face regions were extracted from the detected skin regions. Facial expressions are analyzed from facial images by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images. Radial Basis Function (RBF) Network is used to identify the person and to classify the facial expressions. Our method reliably works even with faces, which carry heavy expressions.