Three Dimensional Modeling of Mixture Formation and Combustion in a Direct Injection Heavy-Duty Diesel Engine

Due to the stringent legislation for emission of diesel engines and also increasing demand on fuel consumption, the importance of detailed 3D simulation of fuel injection, mixing and combustion have been increased in the recent years. In the present work, FIRE code has been used to study the detailed modeling of spray and mixture formation in a Caterpillar heavy-duty diesel engine. The paper provides an overview of the submodels implemented, which account for liquid spray atomization, droplet secondary break-up, droplet collision, impingement, turbulent dispersion and evaporation. The simulation was performed from intake valve closing (IVC) to exhaust valve opening (EVO). The predicted in-cylinder pressure is validated by comparing with existing experimental data. A good agreement between the predicted and experimental values ensures the accuracy of the numerical predictions collected with the present work. Predictions of engine emissions were also performed and a good quantitative agreement between measured and predicted NOx and soot emission data were obtained with the use of the present Zeldowich mechanism and Hiroyasu model. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the internal combustion engine design, optimization and performance analysis.

Structural Analysis of Stiffened FGM Thick Walled Cylinders by Application of a New Cylindrical Super Element

Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Studies on the Blended Concrete Prepared with Tannery Effluent

There is a acute water problem especially in the dry season in and around Perundurai (Erode district, Tamil Nadu, India) where there are more number of tannery units. Hence an attempt was made to use the waste water from tannery industry for construction purpose. The mechanical properties such as compressive strength, tensile strength, flexural strength etc were studied by casting various concrete specimens in form of cube, cylinders and beams etc and were found to be satisfactory. Hence some special properties such as chloride attack, sulphate attack and chemical attack are considered and comparatively studied with the conventional potable water. In this experimental study the results of specimens prepared by using treated and untreated tannery effluent were compared with the concrete specimens prepared by using potable water. It was observed that the concrete had some reduction in strength while subjected to chloride attack, sulphate attack and chemical attack. So admixtures were selected and optimized in suitable proportion to counter act the adverse effects and the results were found to be satisfactory.

Effect of Boric Acid on a-Hydroxy Acids Compounds in Thin Layer Chromatography

In this investigation Salicylic acid, Sulfosalicylic acid and Acetyl salicylic acid were chosen as a sample for thin layer chromatography (TLC) on silica gel plates. Bicarbonate buffer at different pH containing different amounts of boric acid was applied as mobile phase. Specific interaction of these substances with boric acid has effect on Rf in thin layer chromatography. Regular and similar trend was observed in variations of Rf for mentioned compounds in TLC by altering of percentages of boric acid in mobile phase in pH range of 8-10. Also effect of organic solvent, mixture of water/ organic solvent and organic solvent containing boric acid as mobile phase was studied.

Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Preparation of Nanosized Iron Oxide and their Photocatalytic Properties for Congo Red

Nanostructured Iron Oxide with different morphologies of rod-like and granular have been suc-cessfully prepared via a solid-state reaction in the presence of NaCl, NaBr, NaI and NaN3, respectively. The added salts not only prevent a drastic increase in the size of the products but also provide suitable conditions for the oriented growth of primary nanoparticles. The formation mechanisms of these materials by solid-state reaction at ambient temperature are proposed. The photocatalytic experiments for congo red (CR) have demonstrated that the mixture of α-Fe2O3 and Fe3O4 nanostructures were more efficient than α-Fe2O3 nanostructures.

On Uniqueness and Continuous Dependence in the Theory of Micropolar Thermoelastic Mixtures

This paper studies questions of continuous data dependence and uniqueness for solutions of initial boundary value problems in linear micropolar thermoelastic mixtures. Logarithmic convexity arguments are used to establish results with no definiteness assumptions upon the internal energy.

A New Approach for Image Segmentation using Pillar-Kmeans Algorithm

This paper presents a new approach for image segmentation by applying Pillar-Kmeans algorithm. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after optimized by Pillar Algorithm. The Pillar algorithm considers the pillars- placement which should be located as far as possible from each other to withstand against the pressure distribution of a roof, as identical to the number of centroids amongst the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in aspects of precision and computation time. It designates the initial centroids- positions by calculating the accumulated distance metric between each data point and all previous centroids, and then selects data points which have the maximum distance as new initial centroids. This algorithm distributes all initial centroids according to the maximum accumulated distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means and Gaussian Mixture Model algorithm and involving RGB, HSV, HSL and CIELAB color spaces. The experimental results clarify the effectiveness of our approach to improve the segmentation quality in aspects of precision and computational time.

A Growing Natural Gas Approach for Evaluating Quality of Software Modules

The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Analysis and Remediation of Fecal Coliform Bacteria Pollution in Selected Surface Water Bodies of Enugu State of Nigeria

The assessment of surface waters in Enugu metropolis for fecal coliform bacteria was undertaken. Enugu urban was divided into three areas (A1, A2 and A3), and fecal coliform bacteria analysed in the surface waters found in these areas for four years (2005-2008). The plate count method was used for the analyses. Data generated were subjected to statistical tests involving; Normality test, Homogeneity of variance test, correlation test, and tolerance limit test. The influence of seasonality and pollution trends were investigated using time series plots. Results from the tolerance limit test at 95% coverage with 95% confidence, and with respect to EU maximum permissible concentration show that the three areas suffer from fecal coliform pollution. To this end, remediation procedure involving the use of saw-dust extracts from three woods namely; Chlorophora-Excelsa (C-Excelsa),Khayan-Senegalensis,(CSenegalensis) and Erythrophylum-Ivorensis (E-Ivorensis) in controlling the coliforms was studied. Results show that mixture of the acetone extracts of the woods show the most effective antibacterial inhibitory activities (26.00mm zone of inhibition) against E-coli. Methanol extract mixture of the three woods gave best inhibitory activity (26.00mm zone of inhibition) against S-areus, and 25.00mm zones of inhibition against E-Aerogenes. The aqueous extracts mixture gave acceptable zones of inhibitions against the three bacteria organisms.

A Study on the Effects of Thermodynamic Nonideality and Mass Transfer on Multi-phase Hydrodynamics Using CFD Methods

Considering non-ideal behavior of fluids and its effects on hydrodynamic and mass transfer in multiphase flow is very essential. Simulations were performed that takes into account the effects of mass transfer and mixture non-ideality on hydrodynamics reported by Irani et al. In this paper, by assuming the density of phases to be constant and Raullt-s law instead of using EOS and fugacity coefficient definition, respectively for both the liquid and gas phases, the importance of non-ideality effects on mass transfer and hydrodynamic behavior was studied. The results for a system of octane/propane (T=323 K, P =445 kpa) also indicated that the assumption of constant density in simulation had major role to diverse from experimental data. Furthermore, comparison between obtained results and the previous report indicated significant differences between experimental data and simulation results with more ideal assumptions.

Influence of Garbage Leachate on Soil Reaction,Salinity and Soil Organic Matter in East of Isfahan

During this day a considerable amount of Leachate is produced with high amounts of organic material and nutrients needed plants. This study has done in order to scrutinize the effect of Leachate compost on the pH, EC and organic matter percentage in the form of statistical Factorial plan through randomizing block design with three main and two minor treatments and also three replications during three six month periods. Major treatments include N: Irrigation with the region-s well water as a control, I: Frequent irrigation with well water and Leachate, C: Mixing Leachate and water well (25 percent leachate + 75 percent ordinary well water) and secondary treatments, include DI: surface drip irrigation and SDI: sub surface drip irrigation. Results of this study indicated significant differences between treatments and also there were mixing up with the control treatment in the reduction of pH, increasing soluble salts and also increasing the organic matter percentage. This increase is proportional to the amount of added Leachate and in the treatment also proportional to higher mixture of frequent treatment. Therefore, since creating an acidic pH increases the ability to absorb some nutrient elements such as phosphorus, iron, zinc, copper and manganese are increased and the other hand, organic materials also improve many physical and chemical properties of soil are used in Leachate trash Consider health issues as refined in the green belts around cities as a liquid fertilizer recommended.

Reciprocating Compressor Optimum Design and Manufacturing with Respect to Performance, Reliability and Cost

Reciprocating compressors are flexible to handle wide capacity and condition swings, offer a very efficient method of compressing almost any gas mixture in wide range of pressure, can generate high head independent of density, and have numerous applications and wide power ratings. These make them vital component in various units of industrial plants. In this paper optimum reciprocating compressor configuration regarding interstage pressures, low suction pressure, non-lubricated cylinder, speed of machine, capacity control system, compressor valve, lubrication system, piston rod coating, cylinder liner material, barring device, pressure drops, rod load, pin reversal, discharge temperature, cylinder coolant system, performance, flow, coupling, special tools, condition monitoring (including vibration, thermal and rod drop monitoring), commercial points, delivery and acoustic conditions are presented.

Evaluating per-user Fairness of Goal-Oriented Parallel Computer Job Scheduling Policies

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.