Separation and Execution of graphical engine on a cross platform IDE to enhance performance

“Biosim” is a simulation software which works to simulate the harvesting system.This system is able to design a model for any logistic problem with the combination of several objects so that the artificial system can show the performance of an individual model. The system will also describe the efficiency, possibility to be chosen for real life application of that particular model. So, when any one wish to setup a logistic model like- harvesting system, in real life he/she may be noticed about the suitable prostitution for his plants and factories as well as he/she may get information about the least number of objects, total time to complete the task, total investment required for his model, total amount of noise produced for his establishment in advance. It will produce an advance over view for his model. But “Biosim” is quite slow .As it is an object based system, it takes long time to make its decision. Here the main task is to modify the system so that it can work faster than the previous. So, the main objective of this thesis is to reduce the load of “Biosim” by making some modification of the original system as well as to increase its efficiency. So that the whole system will be faster than the previous one and performs more efficiently when it will be applied in real life. Theconcept is to separate the execution part of ”Biosim” form its graphical engine and run this separated portion in a third generation language platform. C++ is chosenhere as this external platform. After completing the proposed system, results with different models have been observed. The results show that, for any type of plants of fields, for any number of trucks, the proposed system is faster than the original system. The proposed system takes at least 15% less time “Biosim”. The efficiency increase with the complexity of than the original the model. More complex the model, more efficient the proposed system is than original “Biosim”.Depending on the complexity of a model, the proposed system can be 56.53 % faster than the original “Biosim”.

Performance and emissions of a gas turbine engine using ox tallow ethyl-ester blended with kerosene

The performance and emissions behavior of a Rover 1S/60 turboshaft engine when operated with several blends of aviation kerosene and ox tallow ethyl-ester are shown in this article. The tests were performed with a compressor shaft coupled to an hydraulic dynamometer where data of power and mass fuel flow were collected to determine the brake specific fuel consumption. A flue gas analyzer was positioned at the exhaust duct to collect oxygen, carbon dioxide, carbon monoxide and nitrous oxides. An increase in the specific fuel consumption was observed due to the lesser lower heating value of the most oxygenated blends. However, reductions of CO, CO2 and NO (x) have been observed and no-significant ill effects have occurred in the turbine operation.

Performance and emissions testing of a small two stroke engine using mid-level ethanol blends

With the introduction of the mid-level ethanol blend gasoline fuel for commercial sale, the compatibility of different off-road engines is needed. This report details the test study of using one mid-level ethanol fuel in a two stroke hand held gasoline engine used to power line trimmers. The study sponsored by E3 is to test the effectiveness of an aftermarket spark plug from E3 Spark Plug when using a mid-level ethanol blend gasoline. A 15% ethanol by volume (E15) is the test mid-level ethanol used and the 10% ethanol by volume (E10) was used as the baseline fuel. The testing comprises running the engine at different load points and throttle positions to evaluate the cylinder head temperature, exhaust temperature and engine speed. Raw gas emissions were also measured to determine the impact of the performance spark plug. The low calorific value of the E15 fuel decreased the speed of the engine along with reduction in the fuel consumption and exhaust gas temperature. The HC emissions for E15 fuel and E3 spark plug increased when compared to the base line in most of the cases and NO formation was dependent on the cylinder head temperature. The E3 spark plug had a tendency to increase the temperature of the cylinder head irrespective of fuel type while reducing engine speed.

Influence of the composition of natural gas-hydrogen blends (HCNG) on performance an CO2 emissions of a spark ignition engine

Addition of hydrogen to natural gas could be a short-term alternative to nowadays fossil fuels as the emissions of greenhouse gases may be reduced. The aim of this study is to evaluate the performance and emissions of a park ignition engine fuelled with pure natural gas, pure hydrogen and different blends of hydrogen and natural gas (HCNG). The increase of the hydrogen fraction leads to variations in the cylinder pressure and CO2 emissions. In this work, a combustion model based on thermodynamic equations is used considering separated zones for the burned and unburned gases. The results show that the maximum cylinder pressure gets higher as the fraction of hydrogen in the blend increases. The presence of hydrogen in the blend leads to a drecrease in the CO2 emissions. Due to hydrogen properties, leaner fuel-air mixtures can be used along with the appropiate spark timing, leading to an engine emissions improvement without a performance worsening.

Optimizing the performance of catalytic traps for hydrocarbon abatement during the cold-start of a gasoline engine

A key target to reduce current hydrocarbon emissions from vehicular exhaust is to improve their abatement under cold-start conditions. Herein, we demonstrate the potential of factorial analysis to design a highly efficient catalytic trap. The impact of the synthesis conditions on the preparation of copper-loaded ZSM-5 is clearly revealed by XRD, N2 sorption, FTIR, NH3-TPD, SEM and TEM. A high concentration of copper nitrate precursor in the synthesis improves the removal of hydrocarbons, providing both strong adsorption sites for hydrocarbon retention at low temperature and copper oxide nanoparticles for full hydrocarbon catalytic combustion at high temperature. The use of copper acetate precursor leads to a more homogeneous dispersion of copper oxide nanoparticles also providing enough catalytic sites for the total oxidation of hydrocarbons released from the adsorption sites, although lower copper loadings are achieved. Thus, synthesis conditions leading to high copper loadings jointly with highly dispersed copper oxide nanoparticles would result in an exceptional catalytic trap able to reach superior hydrocarbon abatement under highly demanding operational conditions.

A study of the performance appraisal interview; a study carried out in the Small Aircraft Engine Department at the Lynn Plant,

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The Corrosion Performance of Magnesium Alloy AM-SC1 in Automotive Engine Block Applications

The magnesium alloy AM-SC1 has been developed as a creep-resistant automotive engine block material. This paper outlines its corrosion performance under laboratory test conditions, considering corrosion on both the external and internal surfaces. This study found that AM-SC1 has a corrosion performance comparable to AZ91 when subjected to an aggressive salt-spray environment or in galvanic-coupling environments. This article further demonstrates that, with the appropriate selection of a commercially available engine coolant, the internal corrosion of AM-SC1 can be maintained at a tolerable level. In addition, internal corrosion resistance can be significantly improved by the addition of fluorides to the coolant solution. It is concluded that AM-SC1 can be successfully used in an engine environment provided that some simple corrosion-prevention strategies are adopted.

Performance, emission and combustion characteristics of an indirect injection (IDI) multi-cylinder compression ignition (CI) engine operating on neat jatropha and karanj oils preheated by jacket water

Renewable non-edible plant oils such as jatropha and karanj have potential to substitute fossil diesel fuels in CI engines. A multi-cylinder water cooled IDI type CI engine has been tested with jatropha and karanj oils and comparisons made against fossil diesel. The physical and chemical properties of the three fuels were measured to investigate the suitability of jatropha and karanj oils as fuels for CI engines. The engine cooling water circuit and fuel supply systems were modified such that hot jacket water preheated the neat plant oil prior to injection. Between jatropha and karanj there was little difference in the performance, emission and combustion results. Compared to fossil diesel, the brake specific fuel consumption on volume basis was around 3% higher for the plant oils and the brake thermal efficiency was almost similar. Jatropha and karanj operation resulted in higher CO 2 and NO x emissions by 7% and 8% respectively, as compared to diesel. The cylinder gas pressure diagram showed stable engine operation with both plant oils. At full load, the plant oils gave around 3% higher peak cylinder pressure than fossil diesel. With the plant oils, cumulative heat release was smaller at low load and almost similar at full load, compared to diesel. At full load, the plant oils exhibited 5% shorter combustion duration. The study concludes that the IDI type CI engine can be efficiently operated with neat jatropha (or karanj) oil preheated by jacket water, after small modifications of the engine cooling and fuel supply circuits. © 2012 Elsevier Ltd.

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

Evaluation of functional performance in commercial buildings

This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Betting on the underdog : bricolage as an engine of resource advantage

Resource-based theory posits that firms achieve high performance by controlling resources that are rare, valuable and costly for others to duplicate or work around. Yet scholars have been less successful understanding processes and behaviours by which firms develop such resources. We draw on the behavioral theory of bricolage from the entrepreneurship literature to suggest one such mechanism by which firms may develop such resource-based advantages. The core of our argument is that idiosyncratic bundling processes synonymous with bricolage behavior may create advantageous resource positions by (i) allowing resource constrained firms to allocate more of their limited resources to activities that they view as more strategically important, and (ii) increasing the difficulties other firms face in trying to imitate these advantages. Based on this reasoning we develop several hypotheses which we test in the context of several samples from a large, longitudinal, Australian study of new firm development. The results support our arguments that bricolage will improve a firms’ overall resource positions while generating more areas of strong resource advantage and fewer areas of strong resource disadvantage. We find little support, however, for our arguments that bricolage will make a firms’ key resource advantages more difficult for other firms to imitate. We find some support for our argument that the role of bricolage in creating resource advantages will be enhanced by the quality of the opportunity with which a firm is engaged.

Review of Engine

Review of Engine by NORPA in Lowdown Spetember 2010

Investigating the performance of automatic new topic identification across multiple datasets 1

Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.