26 resultados para black oil model

em Aston University Research Archive


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Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.

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Visualization has proven to be a powerful and widely-applicable tool the analysis and interpretation of data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualization space. However, for complex data sets living in a high-dimensional space it is unlikely that a single two-dimensional projection can reveal all of the interesting structure. We therefore introduce a hierarchical visualization algorithm which allows the complete data set to be visualized at the top level, with clusters and sub-clusters of data points visualized at deeper levels. The algorithm is based on a hierarchical mixture of latent variable models, whose parameters are estimated using the expectation-maximization algorithm. We demonstrate the principle of the approach first on a toy data set, and then apply the algorithm to the visualization of a synthetic data set in 12 dimensions obtained from a simulation of multi-phase flows in oil pipelines and to data in 36 dimensions derived from satellite images.

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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost and the cumulative effect of failure is determined through probability analysis. The model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.

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Conventionally, oil pipeline projects are evaluated thoroughly by the owner before investment decision is made using market, technical and financial analysis sequentially. The market analysis determines pipelines throughput and supply and demand points. Subsequent, technical analysis identifies technological options and economic and financial analysis then derives the least cost option among all technically feasible options. The subsequent impact assessment tries to justify the selected option by addressing environmental and social issues. The impact assessment often suggests alternative sites, technologies, and/or implementation methodology, necessitating revision of technical and financial analysis. This study addresses these issues via an integrated project evaluation and selection model. The model uses analytic hierarchy process, a multiple-attribute decision-making technique. The effectiveness of the model has been demonstrated through a case application on cross-country petroleum pipeline project in India.

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The literature relating to haze formation, methods of separation, coalescence mechanisms, and models by which droplets <100 μm are collected, coalesced and transferred, have been reviewed with particular reference to particulate bed coalescers. The separation of secondary oil-water dispersions was studied experimentally using packed beds of monosized glass ballotini particles. The variables investigated were superficial velocity, bed depth, particle size, and the phase ratio and drop size distribution of inlet secondary dispersion. A modified pump loop was used to generate secondary dispersions of toluene or Clairsol 350 in water with phase ratios between 0.5-6.0 v/v%.Inlet drop size distributions were determined using a Malvern Particle Size Analyser;effluent, coalesced droplets were sized by photography. Single phase flow pressure drop data were correlated by means of a Carman-Kozeny type equation. Correlations were obtained relating single and two phase pressure drops, as (ΔP2/μc)/ΔP1/μd) = kp Ua Lb dcc dpd Cine A flow equation was derived to correlate the two phase pressure drop data as, ΔP2/(ρcU2) = 8.64*107 [dc/D]-0.27 [L/D]0.71 [dp/D]-0.17 [NRe]1.5 [e1]-0.14 [Cin]0.26  In a comparison between functions to characterise the inlet drop size distributions a modification of the Weibull function provided the best fit of experimental data. The general mean drop diameter was correlated by: q_p q_p p_q /β      Γ ((q-3/β) +1) d qp = d fr  .α        Γ ((P-3/β +1 The measured and predicted mean inlet drop diameters agreed within ±15%. Secondary dispersion separation depends largely upon drop capture within a bed. A theoretical analysis of drop capture mechanisms in this work indicated that indirect interception and London-van der Waal's mechanisms predominate. Mathematical models of dispersed phase concentration m the bed were developed by considering drop motion to be analogous to molecular diffusion.The number of possible channels in a bed was predicted from a model in which the pores comprised randomly-interconnected passage-ways between adjacent packing elements and axial flow occured in cylinders on an equilateral triangular pitch. An expression was derived for length of service channels in a queuing system leading to the prediction of filter coefficients. The insight provided into the mechanisms of drop collection and travel, and the correlations of operating parameters, should assist design of industrial particulate bed coalescers.

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This study has been conceived with the primary objective of identifying and evaluating the financial aspects of the transformation in country/company relations of the international oil industry from the traditional concessionary system to the system of governmental participation in the ownership and operation of oil concessions. The emphasis of the inquiry was placed on assembling a case study of the oil exploitation arrangements of Libya. Through a comprehensive review of the literature, the sociopolitical factors surrounding the international oil business were identified and examined in an attempt to see their influence on contractual arrangements and particularly to gauge the impact of any induced contractual changes on the revenue benefit accruing to the host country from its oil operations. Some comparative analyses were made in the study to examine the viability of the Libyan participation deals both as an investment proposal and as a system of conducting oil activities in the country. The analysis was carried out in the light of specific hypotheses to assess the relative impact of the participation scheme in comparison with the alternative concessionary model on the net revenue resulting to the government from oil operations and the relative effect on the level of research and development within the industry. A discounted cash flow analysis was conducted to measure inputs and outputs of the comparative models and judge their revenue benefits. Then an empirical analysis was carried out to detect any significant behavioural changes in the exploration and development effort associated with the different oil exploitation systems. Results of the investigation of revenues support the argument that the mere introduction of the participation system has not resulted in a significant revenue benefit to the host government. Though there has been a significant increase in government revenue, associated with the period following the emergence of the participation agreements, this increase was mainly due to socio-economic factors other than the participation scheme. At the same time the empirical results have shown an association of the participation scheme with a decline of the oil industry's research and development efforts.

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A number of papers and reports covering the techno-economic analysis of bio-oil production has been published. These have had different scopes, use different feedstocks and reflected national cost structures. This paper reviews and compares their cost estimates and the experimental results that underpin them. A comprehensive cost and performance model was produced based on consensus data from the previous studies or stated scenarios where data is not available that reflected UK costs. The model takes account sales of bio-char that is a co-product of pyrolysis and the electricity consumption of the pyrolysis plant and biomass pre-processing plants. It was concluded that it should be able to produce bio-oil in the UK from energy crops for a similar cost as distillate fuel oil. It was also found that there was little difference in the processing cost for woodchips and baled miscanthus. © 2011 Elsevier Ltd.

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University students encounter difficulties with academic English because of its vocabulary, phraseology, and variability, and also because academic English differs in many respects from general English, the language which they have experienced before starting their university studies. Although students have been provided with many dictionaries that contain some helpful information on words used in academic English, these dictionaries remain focused on the uses of words in general English. There is therefore a gap in the dictionary market for a dictionary for university students, and this thesis provides a proposal for such a dictionary (called the Dictionary of Academic English; DOAE) in the form of a model which depicts how the dictionary should be designed, compiled, and offered to students. The model draws on state-of-the-art techniques in lexicography, dictionary-use research, and corpus linguistics. The model demanded the creation of a completely new corpus of academic language (Corpus of Academic Journal Articles; CAJA). The main advantages of the corpus are its large size (83.5 million words) and balance. Having access to a large corpus of academic language was essential for a corpus-driven approach to data analysis. A good corpus balance in terms of domains enabled a detailed domain-labelling of senses, patterns, collocates, etc. in the dictionary database, which was then used to tailor the output according to the needs of different types of student. The model proposes an online dictionary that is designed as an online dictionary from the outset. The proposed dictionary is revolutionary in the way it addresses the needs of different types of student. It presents students with a dynamic dictionary whose contents can be customised according to the user's native language, subject of study, variant spelling preferences, and/or visual preferences (e.g. black and white).

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The thesis deals with the background, development and description of a mathematical stock control methodology for use within an oil and chemical blending company, where demand and replenishment lead-times are generally non-stationary. The stock control model proper relies on, as input, adaptive forecasts of demand determined for an economical forecast/replenishment period precalculated on an individual stock-item basis. The control procedure is principally that of the continuous review, reorder level type, where the reorder level and reorder quantity 'float', that is, each changes in accordance with changes in demand. Two versions of the Methodology are presented; a cost minimisation version and a service level version. Realising the importance of demand forecasts, four recognised variations of the Trigg and Leach adaptive forecasting routine are examined. A fifth variation, developed, is proposed as part of the stock control methodology. The results of testing the cost minimisation version of the Methodology with historical data, by means of a computerised simulation, are presented together with a description of the simulation used. The performance of the Methodology is in addition compared favourably to a rule-of-thumb approach considered by the Company as an interim solution for reducing stack levels. The contribution of the work to the field of scientific stock control is felt to be significant for the following reasons:- (I) The Methodology is designed specifically for use with non-stationary demand and for this reason alone appears to be unique. (2) The Methodology is unique in its approach and the cost-minimisation version is shown to work successfully with the demand data presented. (3) The Methodology and the thesis as a whole fill an important gap between complex mathematical stock control theory and practical application. A brief description of a computerised order processing/stock monitoring system, designed and implemented as a pre-requisite for the Methodology's practical operation, is presented as an appendix.

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This thesis investigates the cost of electricity generation using bio-oil produced by the fast pyrolysis of UK energy crops. The study covers cost from the farm to the generator’s terminals. The use of short rotation coppice willow and miscanthus as feedstocks was investigated. All costs and performance data have been taken from published papers, reports or web sites. Generation technologies are compared at scales where they have proved economic burning other fuels, rather than at a given size. A pyrolysis yield model was developed for a bubbling fluidised bed fast pyrolysis reactor from published data to predict bio-oil yields and pyrolysis plant energy demands. Generation using diesel engines, gas turbines in open and combined cycle (CCGT) operation and steam cycle plants was considered. The use of bio-oil storage to allow the pyrolysis and generation plants to operate independently of each other was investigated. The option of using diesel generators and open cycle gas turbines for combined heat and power was examined. The possible cost reductions that could be expected through learning if the technology is widely implemented were considered. It was found that none of the systems analysed would be viable without subsidy, but with the current Renewable Obligation Scheme CCGT plants in the 200 to 350 MWe range, super-critical coal fired boilers co-fired with bio-oil, and groups of diesel engine based CHP schemes supplied by a central pyrolysis plant would be viable. It was found that the cost would reduce with implementation and the planting of more energy crops but some subsidy would still be needed to make the plants viable.

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The surface composition of food powders created from spray drying solutions containing various ratios of sodium caseinate, maltodextrin and soya oil have been analysed by Electron Spectroscopy for Chemical Analysis. The results show significant enrichment of oil at the surface of particles compared to the bulk phase, and (when the non-oil components only are considered), a significant surface enrichment of sodium caseinate also. The study found evidence of high levels (80%) of surface fat even on particles of food industry grade (92.5%) sodium caseinate containing only 1% fat.

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This paper examines the implications of the EEC common energy policy for the UK energy sector as represented by a long-term programming model. The model suggests that the UK will be a substantial net exporter of energy in 1985 and will therefore make an important contribution towards the EEC's efforts to meet its import dependency target of 50% or less of gross inland consumption. Furthermore, the UK energy sector could operate within the 1985 EEC energy policy constraints with relatively low extra cost up to the year 2020 (the end of the period covered by the model). The main effect of the constraints would be to bring forward the production of synthetic gas and oil from coal.

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In an Arab oil producing country in the Middle East such as Kuwait, Oil industry is considered as the main and most important industry of the country. This industry’s importance emerged from the significant role it plays in both country’s national economy and also global economy. Moreover, Oil industry’s criticality comes from its interconnectivity with national security and power in the Middle East region. Hence, conducting this research in this crucial industry had certainly added values to companies in this industry as it investigated thoroughly the main components of the TQM implementation process and identified which components affects significantly TQM’s implementation and its gained business results. In addition, as the Oil sector is a large sector that is known for its richness of employees with different national cultures and backgrounds. Thus, this culture-heterogeneous industry seems to be the most appropriate environment to address and satisfy a need in the literature to investigate the national culture values’ effects on TQM implementation process. Furthermore, this research has developed a new conceptual model of TQM implementation process in the Kuwaiti Oil industry that applies in general to operations and productions organizations at the Kuwaiti business environment and in specific to organizations in the Oil industry, as well it serves as a good theoretical model for improving operations and production level of the oil industry in other developing and developed countries. Thus, such research findings minimized the literature’s gap found the limited amount of empirical research of TQM implementation in well-developed industries existing in an Arab, developing countries and specifically in Kuwait, where there was no coherent national model for a universal TQM implementation in the Kuwaiti Oil industry in specific and Kuwaiti business environment in general. Finally, this newly developed research framework, which emerged from the literature search, was validated by rigorous quantitative analysis tools including SPSS and Structural Equation Modeling. The quantitative findings of questionnaires collected were supported by the qualitative findings of interviews conducted.

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This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.