Optimising Depot Storage and Distribution Efficiency through Matching Gasoline Supply to Demand | Chapter 3 | Engineering Research: Perspectives on Recent Advances Vol. 11

 

The primary aim of the study is to optimise depot storage capacity and performance by aligning gasoline supply with distribution requirements. This study was conducted for one of the Nigerian National Petroleum Corporation (refiner) depots supplied by a multi-product (gasoline, diesel and kerosene) pipeline. The depot is supplied by a six-inch multi-product (gasoline, diesel and kerosene) pipeline at 82 m3/hour and loading/distribution of 100 m3/hour per arm inside the depot.

 

The Nigerian National Petroleum Corporation, a refiner, owns and operates a petroleum products pipeline network connected to its 21 storage depots across Nigeria. These storage depots are supplied by a multi-product (gasoline, diesel and kerosene) pipeline network. Since the early 1990s, as gasoline demand increased, the entire supply/distribution chain appeared inadequate. The primary aim of the study is to optimise depot storage capacity and performance by aligning gasoline supply with distribution requirements. This study was conducted for one of the Nigerian National Petroleum Corporation (refiner) depots supplied by a multi-product (gasoline, diesel and kerosene) pipeline. The depot is supplied by a six-inch multi-product (gasoline, diesel and kerosene) pipeline at 82 m3/hour and loading/distribution of 100 m3/hour per arm inside the depot. Distribution/loading facility designed for two arms each for gasoline, kerosene and diesel (or 33.33% for each product), whereas gasoline storage capacity is 55%, diesel, 33%, kerosene 11%, and slops, 1% of the total depot capacity. The design supply to distribution chain capacity ratio showed a mismatch, which in actual operation becomes 2:1. The above design created a ullage problem at sustained supplies, gross under-utilisation of supply chain infrastructures and poor operational performance. After a technical evaluation, a section of the depot storage to loading pipeline network was re-designed and modified to enable product supply capacity to match loading, and minimise storage. Hence, the gasoline loading became 66.67%, kerosene and diesel, each of 16.67%, increasing the actual supply to distribution chain capacity ratio from 2:1 to 2:2 (and when required, can be maximised to 2:3), thereby correcting the apparent mismatch between the supply and distribution chain capacities. Findings showed significant improvement in pipeline transportation scheduling, depot stock and overall product distribution. The modification has enabled the refiner to increase depot and upstream supply chain utilisation.

 

 

Author(s) Details

Eric Obiora Okeke
Nigerian National Petroleum Corporation, PMB 5373, Port Harcourt, Nigeria.

 

Please see the book here :- https://doi.org/10.9734/bpi/erpra/v11/6218

Estimation of the Required Bio-Fuels Substituting Petroleum-Based Fuels in Road-Transportation in the Island of Crete, Greece and Their Climate Change Impacts | Chapter 4 | Contemporary Perspective on Science, Technology and Research Vol. 4

Climate change consists of the most important global environmental problem in our era and its mitigation requires the elimination of the fossil fuels use in all sectors. Transportation consumes large amounts of fossil fuels and has a high share in carbon emissions. According to the current EU policies the conventional vehicles using petrol-based fuels should substitute by 2030 at least 14% of their fuels with bio-fuels including bio-ethanol and bio-diesel. The vehicles in the island of Crete, Greece currently use conventional fuels. The present study investigates the feasibility of substituting 14% of their petrol-based fuels with bio-fuels that could be produced locally. The consumption of gasoline and diesel oil during 2021 in Crete was estimated at 309,766 tons while their carbon emissions at 1,005,182 tnCO2. The required bio-ethanol substituting 14% of the gasoline currently used is estimated at 33,475 tons/year while the bio-diesel substituting the diesel oil at 28,260 tons/year. The annual carbon emission savings due to substitution of conventional fuels with bio-fuels are calculated in the range of 57,207 tnCO2 to 68,105 tnCO2. The land required for the cultivation of the crops producing the abovementioned quantities of bio-fuels corresponds at 4.33% of the total island’s area. The cultivation of energy crops in Crete for bio-fuels production is not foreseen in the future and the required bio-fuels to meet the EU quota should be imported from other territories. It is foreseen that the future de-carbonization in vehicles’ transportation in Crete should be achieved with the electrification of the transportation sector using green electricity generated locally by the abundant solar and wind energy resources.

Author(s) Details:

John Vourdoubas,
107B El. Venizelou Str., 73132, Chania, Crete, Greece.

Please see the link here: https://stm.bookpi.org/CPSTR-V4/article/view/13137

Theoretical and Experimental Validation of Engine Performance and Combustion Characteristics in a Spark Ignition Engine | Chapter 1 | Fundamental Research and Application of Physical Science Vol. 7

 The objective of the study search out validate by test theoretical parameters of efficiency and combustion traits obtained utilizing kiva4. Engine performance is critical in understanding the movement of an internal explosion engine. It is usually presented by characteristic curves or characteristic profiles that are a function of engine limits. Experiments and measurements were performed in an instrument test room in the area of Electrical Engineering at The Copperbelt University in Kitwe Zambia. The engine on that tests were conducted was mounted on a test courtroom and it was fitted accompanying an air-cooled eddy current dynamometer that was able to provide a maximum inexperienced torque of 34 N-m accompanying a precision of ± 0.5%. Test data to substantiate kiva4 simulation results were attended on a 3-cylinder, four-stroke Volkswagen (VW) Polo 6 TSI 1.2 fuel engine. In one set, alternatives in exhaust vapor temperature were intentional by varying the engine load, while custody the engine speed nonstop. In another test, exhaust vapor temperature variations were intentional by keeping the generator at no load whilst varying the speeds. A tertiary experiment examined vacillations in exhaust vapor temperature while the engine was operating under a nonstop load and different weapon speeds. An itape17 file with a 450 uneven mesh was produced using the plain grid/mesh dynamo K3PREP in order to analyse vacillations in exhaust gas hotnesses under test settings. Simulations were so performed established the input parameters settled in the conducted tests. Results presented that, in the first test, power increased accompanying load while specific fuel use reduced and brake warm efficiency improved. In the second test, consume gas hotnesses ranged from 510K to 685K while simulations accompanying the Kiva4 code showed drain gas hotnesses of 507K and 667K at 850rpm and 2500rpm, respectively. In the tertiary test experimental results for the exhaust smoke temperatures were 474K to 575K distinguished with Kiva4 results, of 507K to 667K at 2000rpm and 2500rpm, respectively. Simulations accompanying the kiva4 code presented a significant sameness of the performance characteristics of the power plant. This was evident in the considerable agreement got in the simulation results when compared accompanying the test data, under the thought-out test conditions. The impoverish gas temperature fluctuates contingent upon the engine load and speed as the consume gas temperature increases accompanying increasing speed and load. There are still temperature pulsations, generated by the character and composition of the internal explosion engine, place the individual chambers ignite gradually, and the equivalent temperature pulsations happen in the exhaust pipe. A portion error, between exploratory results and results from simulations with the kiva4 law of only between 2% to 3% was observed.

Author(s) Details:

J. Lungu,
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

L. Siwale,
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

R. J. Kashinga,
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

S. Chama,
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

A. Bereczky,
Department of Energy Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Bertalan Lajos u. 4–6, D208, Hungary.

Please see the link here: https://stm.bookpi.org/FRAPS-V7/article/view/11116

Study on Modeling with Multilayer Perceptron for Detection of Fuel Adulteration Using Python Programming | Chapter 10 | Challenges and Advances in Chemical Science Vol. 6

 Adulteration of fuel is the illegal or unpermitted introduction of an unknown substance into motor spirit, resulting in a product that does not meet the needs and specifications. Normally, cheaper boiling point range hydrocarbons with similar composition are added as additives, causing the quality of the base fuels to be altered and degraded. The trading community uses this approach to make quick unlawful profits. This is due to the fact that tailpipe exhaust from automobiles pollutes the environment and poses a health risk to humans. Fuel pipes leaking exhaust due to illegally added ethanol and methanol to increase octane levels. There must be a proper method for detecting contaminants, both at the laboratory level and at the legislative level. The Artificial Neural Networks technique for analysing fuel adulteration is more precise than any other method currently in use. The gasoline and hydrocarbon fractions are detected in-situ with the help of the Internet of Things, which can be controlled via a remote and data collected via smattering. This information will aid in the detection of contaminants in gasoline and diesel pollutants emitted into the atmosphere via tailpipe emissions. In this paper, we use a cutting-edge computational technique known as Multilayer Perceptron (MLP) to identify impurities in fuels. As a result, global warming and hazardous diseases will be reduced. The multilayer perceptron (MLP) is a type of feed forward artificial neural network that is one of the most efficient techniques for detecting fuel adulterants. For data training, MLP employs the back propagation approach. It has three layers: the input layer, the concealed layer, and the output layer. For the detection and estimate of 3D objects from a single 2D perspective view It is a multilayer perceptron that is employed.

Author(S) Details

U. Vimal Babu
Vignan Foundation for Scientific and Technological Research University, Vadlamudi, Guntur, AP, India.

M. Ramakrishan
Vignan Foundation for Scientific and Technological Research University, Vadlamudi, Guntur, AP, India.

M. Nagamani
School of Computer and Information Sciences, University of Hyderabad, Hyderabad, India

View Book:- https://stm.bookpi.org/CACS-V6/article/view/4356

Study on the Effect of Oxygenated Fuels on Emissions Characteristics: A Comparative Study between Compression Ignition and Spark Ignition Engines | Chapter 5 | New Innovations in Chemistry and Biochemistry Vol. 3

 Petroleum consumption is commonly regarded as one of the most significant factors to environmental degradation. The combustion of oxygenated fuel blends in diesel and gasoline engines is explored in this study, with a special focus on emissions. The study had two objectives: first, to identify the extent to which NOx, uHC, and CO emissions are increased or decreased for various loads in BMEP; and second, to evaluate the extent to which emissions of NOx, uHC, and CO are increased or decreased for various loads in BMEP. Second, the emissions of the two engines should be compared.

In the gasoline engine, 20% methanol was blended with 80% gasoline (M20), whereas in the diesel engine, a mixture of 20% n-butanol and 80% diesel (B20) was investigated. The gasoline engine was a Suzuki RS-416 1.6L normally aspirated engine, and the diesel engine was a 1Z type, 1.9L Turbo-Direct injection engine (TDI). NOx emissions increased with increasing brake mean effective pressure (BMEP) for diesel fuel (DF), but were marginally lower than the blend B20 at 50 and 75 percent load; however, NOx emissions decreased in comparison to gasoline fuel (GF), but were four times higher than in diesel engines. When compared to the reference fuel DF, firing B20 reduced the quality of unburned hydrocarbons (uHC) emissions in diesel engines. The range of uHC emissions in the diesel engine, on the other hand, was much narrower than in the gasoline engine: 10-60 ppm and 600 to 700 ppm, respectively. Above 25 percent BMEP, M20 lowered uHc concentration more than GF. M20's carbon monoxide (CO) concentration increased more than GF's. CO emission concentrations in B20 increased in comparison to DF. All oxygenated blends, M20 and B20, had lower exhaust gas temperatures (EGT) than GF and DF.

Author(S) Details

L. Siwale
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

R. J. Kashinga
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

S. Chama
School of Engineering, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

J. Siame
School of Mines & Mineral Sciences, The Copperbelt University, Riverside Campus, Jambo Drive, Box 21692, Kitwe, Zambia.

A. Bereczky
Department of Energy Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Bertalan Lajos U. 4–6, D208, Hungary.

View Book:- https://stm.bookpi.org/NICB-V3/article/view/4009