Artificial Neural Network and its Applications in the Energy Sector – An Overview

In order to realize the goal of optimal use of energy sources and cleaner environment at a minimal cost, researchers; field professionals; and industrialists have identified the expediency of harnessing the computational benefits provided by artificial intelligence (AI) techniques. This article provides an overview of AI, chronological blueprints of the emergence of artificial neural networks (ANNs) and some of its applications in the energy sector. This short survey reveals that despite the initial hiccups at the developmental stages of ANNs, ANN has tremendously evolved, is still evolving and have been found to be effective in handling highly complex problems even in the areas of modeling, control, and optimization, to mention a few

Mechanisms for Controlling Sand-Induced Corrosion in Horizontal Pipe Flow of Sand, Crude Oil and Water

Background: The presence of sand particles and associated water in crude oil calls for serious concern when the flow conditions leading to flow stratification in an upstream petroleum pipeline become significant. At such conditions, problems such as sand deposition and water containment on the pipe wall may result in consequences such as sand-induced corrosion, mechanical failure, pipe fatigue, reduced flow area, loss of production and pipe blockage which are still currently unresolved by conventional and current models. Objective: A modelling approach was adopted to control the conditions leading to sand-induced corrosion and other related problems caused by flow stratification in the upstream petroleum sector since conventional methods adopted to screen sand, only contribute to the problem. Also, to date, mechanisms and models exist for other corrosion types such as CO2, H2S, acid-induced corrosion, etc. but none currently exists for sand-induced corrosion. However, the concept of force-competition or dimensionless numbers was adopted using a modelling approach to resolve the problem. Method: This research work resolves the situation by means of a three-phase model which incorporates sand, crude oil and water phases in its mass and momentum balance equations while taking into cognisance, the effect of eddies. The three-layer model established in this work, has its origin in a two-phase sand-crude oil system and, based on current literature, a modelling approach that considers the flow of sand, crude oil and water has never been adopted to tackle the problem of sand-induced corrosion caused by associated water as a stimulant for corrosion. Conclusion: The established model gave an accuracy of 99% when results from the model were compared with sand and crude oil production data obtained from the field. Based on the model’s reliability, flow mechanisms/dimensionless numbers were used to ascertain critical flow conditions in order to be able to avoid situations leading to sand deposition, sand-induced corrosion and other related problems. Based on the results obtained, the estimated Euler numbers revealed that the 18 m point of the pipe is at risk due to the impact of the sand-deposit-drag-force on the pipe wall. Also, the estimated Froude numbers were indicative of the 12-18 m points as deposit/corrosion prone areas

Comparative evaluation of processes for production of soybean meal for poultry feed in Nigeria Evaluación comparativa de procesos para la producción de harina de soya para la alimentación de pollos en Nigeria

This work examined and compared three processes for production of low trypsin inhibitor soybean meal. Soybean flour was subjected to roasting, autoclaving and steaming to denature trypsin inhibitors. Roasting was done at 120, 130, 135 and 140 ºC for 5, 7, 8 and 9 minutes, respectively. Autoclaving was carried out at 121ºC, 15psig for 20, 30, 40 and 50 minutes. Steaming was carried out at 105 ºC for 10, 12, 15 and 18 minutes. Defatting of the samples was done and the activity of trypsin inhibitor was investigated. Proximate analysis and quality tests was carried out to ascertain quality of the heat treated soybean meals. Trypsin inhibitor in the soybean meals from the three heat treatment processes ranged from 1.20 to 3.54mg/g while that of raw sample was 6.01mg/g. Percentage crude protein in all the heat treated samples ranged from 39.38 to 40.58 % while that of raw sample was 44.60 %. Urease index ranged from 0.11 to 2.07 % for all heat treated samples while it was 2.11 % for the raw samples. % KOH protein solubility in Soybean meal from the three processes ranged from 45.2 to 73.1 % while that of the raw sample was 49.1%. The results were statistically significant at p>0.05. At significance level of p>0.05 it was established that local soybeans can be processed with adequate heat to obtain low activity soybean meal with good nutrient standard. The steaming process operated at 105 ºC for 18 minutes gave the best overall results with trypsin inhibitor activity of 1.20 mg/g

A study of LNG processes to determine the effect of end flash systems on efficiency

This paper describes the simulation, exergy analysis and com- parison of two commonly applied liquefaction of technologies natural gas, namely: propane precooled mixed refrigerant process (C3MR) and dual mixed refrigerant process (DMR) alongside two modifications of each em- ploying end flash systems. The C3MR and DMR process schemes were simulated using the commercial software to mathematically model chemi- cal processes. These schemes were then analysed using energy and exergy calculations to determine their performances. The exergy efficiency for the C3MR processes without end flash system, with simple end flash system and extended end flash system were evaluated as 29%, 31%, and 33%, respec- tively, while the exergy efficiency for the DMR processes without end flash system, with simple end flash system, and extended end flash system were evaluated as 26%, 25.5%, and 30%, respectively. The results achieved show that the extended end flash system versions of the schemes are most effi- cient. Furthermore, the exergy analysis depicted that the major equipment that must be enhanced in order to improve the cycle exergy efficiencies are the compressors, heat exchangers, and coolers

Prediction of sand kinematic pressure and fluid-particle interaction coefficient as means of preventing sand-induced corrosion in crude oil pipelines

Sand-induced corrosion and scaling of petroleum pipes is a serious situation that barely knows any solution by conventional or new methods of corrosion control. This is because, the mechanism behind sand corrosion and scaling of petroleum pipes is yet to be unravelled. Rather than avoid the situation, the integration of sand filters in petroleum lines also contribute to the problem. In this work, a three phase model was used to simulate upstream flow conditions where sand is produced alongside water and crude oil. The effects of fluid-particle interaction coefficient/forces and sand kinematic pressure, in relation to conditions that favour sand deposition, corrosion and scaling of petroleum pipes were determined. Based on the results, on a 2–3 h basis, periodic checks need be conducted at the 12–18 m points where sand kinematic pressures and interaction coefficients of the components require flow adjustments in order to avoid situations leading to pipeline we

Thermodynamic Analysis of Raw Mill in Cement Industry Using Aspen Plus Simulator

This study investigates the appropriateness of exergy calculation using Aspen Plus Process Simulator which has a robust data library and powerful engineering calculation capabilities. The simulator was used for the thermodynamic performance of a raw mill (RM) and raw materials preparation unit in a cement plant in Nigeria using actual operating data. The raw mill has a capacity\ud of 240,000 kilogram-material per hour. Also, both exergy and exergetic efficiency of raw mills from three literature sources were investigated and compared with the simulation results from Aspen Plus process model. The results were subjected to statistical analysis using ANOVA. The exergy efficiency for the raw mill studied using Aspen plus simulator modelling technique was found to be 21.4%. It was found that the difference in exergy efficiencies of the simulation results of the three-literature data vary within ±2.5% of the published results. The present method using the Aspen plus simulator is suggested as a useful tool in making informed decisions for developing energy policies and exergy utilization, providing energy conservation measures in improving the efficiency of the system

Prediction of global warming potential and carbon tax of a natural gas-fired plant

Industrial activities, including the process of power generation from thermal plants, are inevitably associated with the generation of gaseous wastes and particulate matters. Industrial activities, therefore, contribute largely to the emission of environmental pollutants. In addition to causing environmental degradation, the emission of pollutants, particularly greenhouse gases, have far-reaching social negative externalities, mainly in the area of unconducive temperature rise and adverse climatic impact. The unintended impacts of industrial emissions have motivated the development of plans and strategies for their abatement. In this study, predictive models of the global warming potential and carbon tax of the gaseous emission at various fuel consumption levels and different air–fuel ratio for the combustion process in a thermal power plant were developed. It is expected that the models serve as a veritable tool for projecting the environmental & economic costs of natural gas burning and optimizing the process of the fuel combustion for lower greenhouse gas emissions

Modelling the power output from a steam power plant in Nigeria

Adequate supply of electricity at a competitive price is pivotal to sustainable development. More often than not, the generation of electricity which drives modern growth and development is currently powered by limited fossil fuels in many nations. Electricity generation and megawatt demand are also usually fluctuating due to several pertinent factors. In a bid to articulate the impact of inherent variations in process parameters on the performance of steam power plant at different loads, this paper presents an investigation into the efficacy of two validation strategies in predicting the net power output from the plant using GMDH Shell software. Using the combinatorial algorithm, the k-fold cross-validation strategy and the training/testing validation technique were applied to empirical data of a power plant in Nigeria. The performance of the models returned from the two validation strategies was evaluated using maximum negative error, maximum positive error, mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), residual sum, the standard deviation of residuals, coefficient of determination (R2) and correlation. For the number of folds and the training/testing split percentage considered in this study, results show that both models obtained were quite competitive, with the k-fold model having a slight edge over the other model. It is expected that the outcome of the study will be handy in researches for providing knowledge base information on choosing and setting optimum operating conditions at various load demand

Thermodynamic assessment of crude distillation units: case studies of Nigeria refineries

This paper presents the results of thermodynamic analysis of the crude distillation units of two refineries in Nigeria. The analysis was intended to assess the thermodynamic efficiencies of the refineries and proffer methods of improving the efficiencies. Presented results show the atmospheric distillation units of the refineries have 33.3% and 31.6% exergetic efficiencies and 86.5% and 74.6% energetic efficiencies, respectively. Modifications of the operating and feed conditions of the refineries resulted in increased exergetic efficiencies for as much as 62.3% and 38.7% for the refineries. Thermodynamic analysis of the refineries can bring about efficiency improvement and effectiveness of the refineries