Development of a Real–Time Petroleum Products Aduteration Detector

2021 ◽  
Author(s):  
Olabisi Olotu ◽  
Sunday Isehunwa ◽  
Bola Asiru ◽  
Zeberu Elakhame
Keyword(s):  
Real Time ◽  
Binary Mixtures ◽  
Chemical Properties ◽  
Petroleum Products ◽  
Fuel Oil ◽  
Lubricating Oil ◽  
Pure Liquid ◽  
Mixing Rule ◽  
Real Time Detection ◽  
Solid Particulates

Abstract Adulteration of petroleum products with the resultant safety, health, environmental and economic impact is a challenge in Nigeria and many developing countries. While the commonly used techniques by regulatory agencies and some end-users for quality assurance of petroleum products are time-consuming and expensive. This study was therefore designed to develop a device for real-time detection of petroleum products adulteration. Samples of petrol, diesel and kerosene were collected; samples of water, naphtha, alcohol, pure and used lubricating oil, and High Pour Fuel Oil (HPFO) were collected and used as liquid contaminants while saw dust, ash and fine sand were used as solid particulates. At temperatures between 23-28°C (1°C interval), binary mixtures were prepared using the pure products with liquid contaminants (95:5, ..,5: 95 V/V) and with particulates (0, 2, 4, 6, 8,10 g). New mixing rules were developed for the SG and IFT of the binary liquid mixtures and compared with Kay mixing rule. Developed mathematical models of the physical-chemical properties were used to simulate a meter designed and constructed around a microcontroller with multiple input/output pins and a load cell sensor. The SG and IFT of the pure liquid and solid binary mixtures ranged from 0.810 to 1.020, 25.5 to 47.2 dynes/cm and 0.820 to 1.080 and 26.3 and 50.2 dynes/cm respectively. For products contaminated with solid particulates, SG varied between 0.860 and 0.990. The new mixing rule gave coefficient of 0.84 and 27.8 for SG and IFT compared with 0.83 and 25.6 of Kay's model. Adulteration of products was detected at 20-30% by volume and 10-20% by mass of contamination, and displayed RED for adulterated samples, GREEN for pure samples and numerical values of SG in digital form which were within ±0.01 % of actual measurements. A device for real-time detection of adulteration in petroleum products was developed which can be adapted to real-time evaluation of similar binary mixtures.

scholarly journals Simulation of the circulation method for discharging viscous petroleum products

2020 ◽  
Vol 6 (2) ◽  
pp. 94-105
Author(s):  
Tatiana S. Karpova ◽  
Vladimir I. Moiseev ◽  
Vera A. Ksenofontova
Keyword(s):  
Chemical Properties ◽  
Simulation Models ◽  
Petroleum Products ◽  
Fuel Oil ◽  
New Method ◽  
Winter Period ◽  
Discharge Process ◽  
Cost Of Transport ◽  
Circulation Method ◽  
The Cost

Background: In the domestic market, the consumption of fuel oil increases during the winter period, leading to higher prices. At the same time, the cost of inputs and the time for the discharge of viscous oil products are greatly increased. The duration of the discharge process is related to the physico-chemical properties of the fuel oil. Its viscosity depends on the temperature of the product itself and the temperature of the environment, which in our country averages 5.5 C per year. Aim: Reduction in the length and cost of transport of viscous petroleum products. Methods: The article proposes a new method for the carriage of viscous petroleum products by rail, ensuring that their fluidity is preserved without the use of thermal insulation of the boiler of the tank-wagon and the means for carrying the heating. Simulation models of the processes of pouring out viscous petroleum products for a traditional and new method of pouring in the circulation method of discharge of viscous petroleum products, which make it possible to estimate the quantity of resources consumed, are constructed. Results: The work shows the peculiarities of the existing process of discharging viscous petroleum products. Simulation and functional-cost analysis of the discharge process were carried out under the circulatory method for heating viscous petroleum products. The results were compared. Conclusion: In the new pouring method, the discharge process is similar to the summer period.

Real-Time Detection of Drowsiness Related Lane Departures Using Steering Wheel Angle

2012 ◽  
Author(s):  
Anthony D. McDonald ◽  
Chris Schwarz ◽  
John D. Lee ◽  
Timothy L. Brown
Keyword(s):  
Real Time ◽  
Steering Wheel ◽  
Real Time Detection

Methodological approaches to modeling the conditions for the formation of technological losses of oil and petroleum products due to evaporation from tanks

2020 ◽  
Vol 10 (4) ◽  
pp. 386-393
Author(s):  
Кonstantin Е. Lesnykh ◽  
◽  
Aleksey А. Korshak ◽  
Nafis N. Khafizov ◽  
Andrey A. Kuznetsov ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Petroleum Products ◽  
Quantitative Composition ◽  
Number Of Factors ◽  
Main Pipelines ◽  
Pumping Rates ◽  
Mathematical Relationships ◽  
Physical And Chemical ◽  
Storage Temperatures ◽  
And Chemical Properties

The conditions for the formation of technological losses of oil and petroleum products during transportation through the main pipelines are considered and it is established that the main sources of these losses are large and small airflows of reservoirs. The value of technological losses from evaporation from tanks depends on a large number of factors, in particular: storage temperatures, pumping rates, tank filling heights, physical and chemical properties of the transported liquid, tanks turnover. Until now, a unified approach to the procedure for determining the qualitative and quantitative composition of technological losses from the evaporation of hydrocarbons during storage has not been developed, which leads to disagreements in assessing the actual losses of energy carriers. According to the analysis, it was found that the best is the calculation method for determining the actual irrecoverable losses of hydrocarbons. Its application involves the use of mathematical relationships that describe the dynamics of evaporation of oil and petroleum products in real conditions. To establish such relationships, it is proposed to develop and implement a unit that enables simulation of the process of evaporation from tanks under various conditions and obtaining experimental data taking into account a combination of a variety of factors that affect the amount of the technological losses.

Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks

2020 ◽  
Vol 16 (5) ◽  
pp. 584-591 ◽  
Author(s):  
Muhammad Hanif Ahmad Nizar ◽  
Chow Khuen Chan ◽  
Azira Khalil ◽  
Ahmad Khairuddin Mohamed Yusof ◽  
Khin Wee Lai
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Heart Disease ◽  
Aortic Valve ◽  
Real Time ◽  
Convolutional Neural Networks ◽  
Valvular Heart Disease ◽  
Detection System ◽  
Processing Unit ◽  
Real Time Detection

Background: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular heart disease. However, the images from echocardiogram are poor in comparison to Computerized Tomography and Magnetic Resonance Imaging scan. This study proposes the development of Convolutional Neural Networks (CNN) that can function optimally during a live echocardiographic examination for detection of the aortic valve. An automated detection system in an echocardiogram will improve the accuracy of medical diagnosis and can provide further medical analysis from the resulting detection. Methods: Two detection architectures, Single Shot Multibox Detector (SSD) and Faster Regional based Convolutional Neural Network (R-CNN) with various feature extractors were trained on echocardiography images from 33 patients. Thereafter, the models were tested on 10 echocardiography videos. Results: Faster R-CNN Inception v2 had shown the highest accuracy (98.6%) followed closely by SSD Mobilenet v2. In terms of speed, SSD Mobilenet v2 resulted in a loss of 46.81% in framesper- second (fps) during real-time detection but managed to perform better than the other neural network models. Additionally, SSD Mobilenet v2 used the least amount of Graphic Processing Unit (GPU) but the Central Processing Unit (CPU) usage was relatively similar throughout all models. Conclusion: Our findings provide a foundation for implementing a convolutional detection system to echocardiography for medical purposes.

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