RJPGT 2023

The assurance of the electric power quality and the monitoring of the level of disruptive emissions determine that the problems related to the limitation of electrical disturbances become one of the important concerns of the electrical energy specialists. The paper presents both the results of a laboratory study on how the frequency converters influence the level of voltage and current harmonics at the output of the converters, and the results and conclusions of the measurements that highlight the major improvement brought to the power quality indicators by equipping with an active filter the supply circuit of a high-power electric drive powered by a frequency converter. An important conclusion of the paper is that before making the decision to mount filters to limit the level of distortion, it is necessary to make a careful analysis of the solutions regarding the reduction of distortion even at the level of the disruptive equipment. Only if these measures are not enough, the solution of using active filters, although expensive, is very effective.

In this paper, the current heat recovery system from delayed coking in a Romanian refinery is analyzed, the current system is simulated, and an additional heat recovery variant is proposed and simulated. Currently, the raw material is preheated with the following hot streams: light and heavy diesel (LDO and HDO) as final products of the plant and recirculated heavy diesel (RDO). After preheating the raw material, the final temperatures of the hot process streams indicate a thermal energy reserve that can be harnessed. Hot technological flows, after preheating the raw material, pass through air coolers, thus a large part of the thermal energy is lost in the environment. Since the temperature level of the hot technological flows is quite high after the preheating of the raw material - the outlet temperatures LDO is 167°C, HDO is 277°C and RDO is 245°C - the paper proposes two options for recovery of the heat from technological flows that have a reserve of thermal energy, obtaining low-pressure saturated steam. The simulation of raw material preheating systems, the actual and the proposed variant, were made with the PRO/II software.

The Moesian Platform pertaining to Romania gathers numerous petroleum and gas reservoirs of various sizes and types of hydrocarbons, from black oil to shallow gas reservoirs. They are sited in reservoir rocks having different lithologies (limestone, sand, sandstone, microconglomerate etc) belonging to different ages from the Cretaceous up to the late Pliocene, all formations being characterized by the Paleogene hiatus. Sand formations studies for certain reservoirs indicate oceans rivers and deltas as depositional environments although lithologic analysis, and especially paleontological analysis, are very limited (sometimes missing) and could not be used to re-enact a detailed image. Using granulometric analysis performed on sand cored from different wells, clarification is brought onto the paleoecology of the zone and thus it was discovered which wells belonged to the ocean riverbed and riverbank. Paleoenvironmental studies require large quantities of data which in many cases are not available, but they help in clarifying further aspects such as regional geology, depositional environments and ultimately reservoir heterogeneity which would, in term, justify different production behaviors of the oil reservoirs. Production data has not been studied for this application, but it is confirmed to have ample fluctuations and wells on this structure require workover intervention very often. For data interpretation the classic Udden-Wentworth scale is used along with granulometries from different surface sites and artificial sand having one of the conclusions that the analyzed sand fits almost on the dot on the assumed paleoenvironment.

In the latest years, the need of new technologies in the industrial environment has increased due to the need of a more cost efficient, resilient, and sustainable production process. One of the main issues that is addressed in this research work is the lack of a technology that allows prediction and prevention of the breakdowns of a production line using digital models and artificial intelligence to take the best decisions based on real-time data. This paper presents a method for collecting data from the production line and feed these data to a database used by the Digital Twin model created in Matlab Predictive Maintenance Toolbox in which, based on this data, a decision about the maintenance activities required will be taken. This approach generates significant value by assisting maintenance engineers in pinpointing the precise timing for equipment maintenance. This capability directly contributes to reducing production line downtime and minimizing failures. Also, the Digital Twin model can be used to enable and test adjustments to the parameters of the production line equipment in order to determine the impact of this changes of the production process without interfering with the production process itself.

This paper deals with the comparative study of the dispersion of some components of flue gases in the atmosphere. Mathematical modelling of the dispersion of pollutants discharged from technological furnaces in refineries is carried out using high-performance software. Thus, taking into account the meteorological conditions and the pollutant concentrations, the level of atmospheric pollution can be determined. The aim of the paper is to compare the values of NO2 and CO concentrations obtained with the classical Gaussian dispersion model algorithm with the values of pollutant concentrations estimated using the SCREEN View simulation software. The determinations were made taking into account receivers located at distances of 100 m, 500 m, 2500 m and 5000 m from the emission source, thus it was established at which distance from the source the maximum pollutant concentrations resulted. For atmospheric stability class, A and F (very unstable and stable). For A stability class, the maximum concentrations pollutant resulted at a distance of 500m from the emission source, and for F stability class, the maximum pollutant concentrations resulted at a distance of 2500 m from the emission source. Both with the classic work methodology and with the SCREEN View software, the concentration values are comparable, this underlines the precision of the software. Also, with the classic Gaussian modelling algorithm, the maximum height of the smoke plume was calculated. This is higher for stability class A, compared to F.

In the current context of promoting the large-scale use of renewable energy, the installation of wind turbines in the offshore and onshore environments is opportune. According to statistics, in 2022 offshore wind installations generated 21 GW, respectively 22.3% of a total of 94 GW produced by all offshore and onshore wind installations. This contribution was, also, estimated to increase in the coming years. In the Romanian sector of the Black Sea, the first wind farm will be installed in four years, according to the Romanian Ministry of Energy. Therefore, in our paper, we start with a short presentation of the different support types of the offshore wind turbine. According to the specialized literature, we found that the monopile has the simplest construction and is the most used in water with a depth of less than 50m. Further, we show theoretical aspects regarding the wave parameters and kinematics, wave spectra, wave forces, and overturning moments that act on a monopile in different conditions. Based on a Black Sea dataset and working scenarios, we performed several sensitivity studies on wind turbine support dimensions, wave characteristics, wave forces, and overturning moments. Finally, the variation ranges of wave forces and overturning moments will be estimated, under the environmental conditions of a Black Sea sector for different sizes of a monopile. These are useful in the design of an offshore wind turbine.

The batch adsorption of 2,4-dichlorophenol from aqueous solution onto mesoporous activated carbon was investigated for a range of initial concentrations of 50 to 1000 mg/ L, at constant temperature of 293 K. The experimental adsorption isotherms were analyzed with two and three parameters models (i.e., Freundlich, Langmuir, Langmuir-Freundlich, and Brouers-Sotolongo models). The non-linear fitting method was employed for estimating the isotherm parameters. The standard statistical tools were used to check the accuracy of the fit measure, namely: the coefficient of determination R2, the adjusted coefficient of determination Adj- R2, the residual sum of squares RSS (or chi-square function χ2), and reduced chi-square Red- χ2. The analysis of all the isotherms found that the Brouers-Sotolongo model shows higher correlation coefficients of R2 and Adj-R2 values and lower values of RSS and Red-χ2. Also, the Brouers-Sotolongo model shows a maximum adsorption capacity qm of 50.46 mg/g, which is very close to the experimental data (48.123 mg/g) value. The adsorption process was mainly physical adsorption on heterogeneous surfaces. The heterogeneous surface of activated carbon was confirmed by FT-IR analysis, the Boehm method, and pHPZC, as presented in our previous studies. The interactions between 2,4 DCP and GAC are mostly a type of dispersion effect between the π electrons in the aromatic ring of the phenolic compound and the π electrons in the structure of the GAC adsorbent. Also, electrostatic attractions may occur between the π electrons in the aromatic rings of 2,4 DCP and the positive surface of the GAC.

The flow of petroleum fluids through extraction pipes is a phenomenon difficult to describe in mathematical terms. Complex numerical relationships are usually used, most of which are derived from observation of wells in operation and analysis of collected production data, and others are determined from laboratory experiments. But a model that uses artificial intelligence in this field has not been created to date, even if this concept is widely used in the oil industry. This is precisely why this article proposes a numerical model based on artificial intelligence that determines the flow equations and their limits according to the type of flow, determines the relative velocities of gas and oil liquids during the ascent through the extraction pipes and also statistically analyzes the data obtained as a result of applying the described model with real data collected from a group of wells in production.

Oil refineries and petrochemical facilities contribute to the pollution of the environment either air, water, or soil releasing hazardous and toxic air pollutants into the atmosphere. These include nitrogen oxides (NOx), carbon monoxide (CO), hydrogen sulfide (H2S), sulfur dioxide (SO2), and particulate matter (PM), affecting both environment and human health. In the range of air pollutants, hydrogen sulfide is less monitored and reported despite its importance in determining adverse effects. Background H2S concentrations in air were found to range commonly from 0.11 ppb to 0.33 ppb. The concentrations in urban areas can reach 1 ppb (~1.4 g m-3) up to more than 90 ppb (~125 g m-3) near sources of H2S emissions. In Romania, the standard for the air in protected areas for the hydrogen sulfide pollutant provides an admissible concentration, over a maximum interval of 30 minutes, of 15 µg/m³. Everything that exceeds this value is considered harmful to human health. The statistics for the H2S time series recorded in Ploiești City by the mobile laboratory of the Environmental Protection Agency Prahova between 2019 and 2021 with a sampling rate of 30 minutes showed that the mean ranged between 1.51 and 3.74 µg/m³, while the maximum reached 59.36 µg/m³ in the east of Ploiești in 2019. Overall, the highest variance occurred in the East and North parts due to the presence of the concentration peaks. Hydrogen sulfide must be considered on the public health agenda, both from the occupational perspective and for the ambient concentrations near significant H2S sources and in background urban areas. The monitoring infrastructure needs to be improved to allow continuous surveillance to ensure reliable databases that support research regarding the health effects of H2S across the concentrations occurring in the urban environment.

The purpose of this work is to design and implement a cascade control system of the level with the flow rate, with remote supervision, in an industrial type installation, located in the Laboratory of Measurement Techniques, Department of Automation, Computers & Electronics, within the Faculty of Mechanical and Electrical Engineering. The operating parameters of the installation are as follows: suction pressure: 0 – 2 bar; discharge pressure: 0 -10 bar; water flow: 0-30 m3/h; transported liquid: water. The automation system is structured on three hierarchical levels: level 1: the instrumentation mounted on the installation (transducers, signaling devices, etc.); level 2: includes the TGA System; level 3: constitutes the upper hierarchical level and includes the HMI (Human Machine Interface). The TGA system is a computerized system that ensures the monitoring, command and control functions of all the stand's component elements. It contains a programmable logic controller PLC 1214 – Siemens, which communicates via an Ethernet IP network with an operator interface and with the network of the Faculty of Mechanical and Electrical Engineering, which allows remote control of the installation. It also includes the protection system in case of failure, which involves stopping the rotating equipment, isolating the pipes by closing the control valve and alarming the operators. The HMI (Human Machine Interface) interface presents 3 options on the start page, from where the operator can select which application he wants to test: flow control loop application; level adjustment loop application; cascade adjustment loop application. The HMI equipment integrates SCADA functions, database update, evolution curves of analog quantities, sound and monitor alarm system, keyboard command, periodic records, event records, alarm records and technological schemes at the human-machine interface. The entire software is made in an open architecture, recommended by ISO norms. The PLC communicates in the network by adopting the protocol TCP/IP. An executable program used for the real-time application program was developed.

In the current era of advanced digital technologies, form recognition is integrated into numerous applications, from computer vision to industrial automation. This paper focuses on a comparative analysis of two distinct form recognition algorithms, namely harnessing the power of artificial intelligence (AI) and image processing techniques. The research is motivated by the need to address the trade-off between speed and complexity in form recognition, with a center on real-world applicability. Traditional image processing-based form recognition approaches often require complex coding, substantial domain expertise, and significant computational resources. This complexity can hinder rapid adaptation to changing requirements and the addition of new forms. The aim is to explore whether AI-powered algorithms can offer a more efficient and versatile alternative, reducing the barriers to entry for form recognition tasks. The primary goal of the paper is to compare the performance of AI-based form recognition with image processing-based methods in terms of speed and accuracy. The second goal is to assess the ease of adapting AI-based algorithms to new forms without extensive code changes. Two form recognition algorithms were designed and implemented, one based on artificial intelligence and a second relying on image processing. The AI-powered algorithm uses neural network architecture trained on a predefined dataset of forms. The image processing algorithm employs edge detection and contour analysis techniques.

With a strong focus on optimizing the performance of a producing well, our work performs a nodal analysis of the subsurface production subsystem. Using data from the Kinkasi-C1 well on the Kinkasi field, producing in the Vermelha, it analyses the elements of this subsystem, focusing on the analysis of head losses in the production tubing. Knowing the daily production rate and having determined the inflow performance relationship (reservoir pressure and physical properties of the fluids), the wellhead pressure that was lacking was determined. Starting from the pressure node at the bottom of the well, the Poettmann & Carpenter correlation provided us with the head losses along the tubing and, in turn, the wellhead pressure for the company's daily flow rate. Given that this correlation requires tedious calculations, we used Java programming to develop software to support its calculation algorithm. After this stage, the possibility of producing more with or without activation was studied. By prioritizing oil production, activation by pumping, more specifically using an ESP, was the appropriate means of optimizing KK-C1's performance.

Drilling consists of the operation of creating a well, which involves a complex set of activities. In a narrower sense, it includes the dislocation of rocks and the extraction of rock fragments to the surface. A drilling tool called a bit is used to dislodge rocks, being connected to the surface drilling rig via a drill string. Automating the processes associated to drilling is extremely important to ensure its development in optimal conditions. This work is focused on the control of the drilling hoe rotation speed, in order to damage it as little as possible.

The informational growth dramatically changed the standard form of publication, access, and use of scientific information. Due to Internet, scientific publications migrated from the traditional to a digital configuration. Common users, as well as highly trained professionals from various fields, aim to retrieve information in the shortest possible time, but in the context of an unprecedented growth of data volume, big difficulties occur in finding and accessing the available information, resulting in stress and important delays in decision making. Therefore, training courses in information culture are organized in university libraries, particularly for a superior efficiency of scientific data bases usage. The paper presents an introduction to the architecture of a retrieval information system and a study of the most popular search engines and of the indexing process. Hereinafter, a Page Rank algorithm implementation is performed and a comparative study relative to different search engines is conducted, emphasizing the specific advantages and disadvantages.

Seawater desalination is a technology with a high-speed evolution for obtaining drinking water from seawater, especially in vulnerable areas of the globe. Reverse osmosis is the most used technology and is supported by the commercial development of many types of membranes widely used in desalination. However, there are no general rules for membrane selection. A single criterion is generally accepted: the membrane's permeability to the salts in the feed (generally to sodium chloride). This article has three specific aims: 1) experimental determination of the salt content of the water of four selected seas (i.e., Paralia Katerini – Greece, Civitavecchia – Italy, Tunis – Tunisia, and Manifah – Saudi Arabia). 2) from an extensive range of commercially available membranes, after consulting several "technical data sheets", four types of membranes were selected for this study: Hydranautics SWC6 - LD, Koch TFC - HF - 8", Toray TM820V - 400. Our calculation regarding their permeabilities led to values in the range of 0.61 liter/m2·h·bar to 1.87 liter/m2·h·bar. 3) for each selected membrane, the total area required in a RO plant to obtain a permeate flow of 1 000 m3/day and a salt concentration in the permeate of 225 ppm was calculated for an operating pressure in the range of 35 bar to 65 bar, for operating temperature in the range of 20°C to 50°C and for seawater salinity in RO feed in the range of 30 000 ppm to 50 000 ppm. The concentration of salts in the feed and the operating pressure have the most significant influence on the increase in the total area of the membranes in the reverse osmosis plant.

Checking the nutrient content of the soil after applying a depollution method has a significant impact on the environment. Of the macroelements present in the soil structure, those of particular interest are nitrogen, phosphorus and potassium. The presence of each element in the soil structure is important for plant growth on depolluted soils. Nitrogen absorbed from the soil is transformed through various chemical reactions into assimilable amino acids that ensure the growth of leaves, stems and the development of the plant root system. Phosphorus, assimilated by plants in the form of phosphoric acid or phosphoric anhydride, is involved in the functioning of the immune system, increasing the plant's resistance to crop conditions, atmospheric conditions, pest attack and insecticide administration. Potassium is converted during chemical reactions into potassium hydroxide and assimilated in this form by the plant. It increases the plant's ability to store nutrients in its reserve organs. Electrical desorption remediation is recommended as a remediation method for soils contaminated with volatile or semi-volatile compounds. The extraction yield of pollutants from soil is around 95%, lower values are only obtained if the mass content of pollutants in the soil is higher than 10%. Following the application of desorption depollution, the only element that does not undergo transformation is potassium, which makes this method of depollution preferred, despite being expensive.

The paper presents the research of the author in developing an application for sizing and selection of control valves for typical process control applications. The proper sizing, selection, installation, and maintenance of control valve are all significant to obtain precise control performance. The paper has three parts. The first part describes the steps necessary to size and selection control valve based on the specific standards. The second part is destined to present the application developed by the author using Python programming language. In the last part, the author has presented and analyzed the numerical results of selection control valve using data from a real process.

Coiled tubing is used in oil and gas well production with the aim of increasing oil field production. The efficiency of this process is reproduced in this material, with practical applications in carbonate rocks, also presenting the conditions of applicability of the method (the maximum friction coefficient, the optimal depth of the intervention zone, the working conditions during the operations to increase the recovery). The surface weight variation graphs with depth are also shown (Theoretical lockup and Predicted surface weight during CT-RIH and CT-POOH considering default values for the coefficients of friction for 8.5-in OH section and 6-in OH section). The 55% increase in well productivity after using this technique makes the coiling tube useful at over 1000m depth.

The control of the pH neutralization process has a decisive role in many industrial branches, as: wastewater treatment, biotechnology, pharmaceutical industry, chemical processing, etc. However, the pH neutralization process is a difficult one to control, due to time-varying process parameters, its high non-linearity and to the sudden variation of the pH around the equivalence point. The paper presents a device and an integrated application that uses artificial intelligence (IA) developed for dosage of the necessary reactants in wastewater pH control. The AI techniques were integrated into the application by developing an expert system (ES). For this purpose, were used the necessary if-then rules (rules that make up the inference engine (IE) of the ES) related to the flowrates of the reactants necessary for wastewater pH neutralization. The ES knowledge base (KB) was built based on the recorded pH values. The hardware component (the device) was created using the Arduino equipment.

In the process of tertiary migration of crude oil, the phase that occurs after the cessation of primary exploitation of petroleum fluid deposits, the deposit is characterized by a state of maximum discontinuity of microscale phases and their abnormal gravitational positioning. This is precisely why it is necessary to discuss the blocking/unblocking mechanisms of wetting phase and non-wetting phase plugs in/out of capillary microtraps. The article presents for the first time a microfluidic behavior of crude oil through cores, with the analysis of polymer flow through rock pores and their filling with petroleum fluids.

Artificial neuronal networks (ANNs) are rapidly becoming a very useful tool in the petroleum industry for predicting different evolution types for different parameters and use the human nervous system principles in creating the required prediction algorithm. Main objective of paper is to use a feedforward neural network to estimate the distribution of initial water saturation, as a small part of reservoir characterization in the presence of heterogeneities. It is very known that ANNs are complicated structures, take a long time in programing, are computer-time consuming and often require specialized aid in using them. Therefore, it will be an asset to know if reservoir heterogeneities can be pointed out with ANNs, or other prediction methods are indicated for these cases.

The paper presents an application that involves the real-time acquisition of four parameters: temperature, relative humidity, pressure and light intensity. Several sensors are used that acquire these values (DHT11- temperature and relative humidity, BMP180 - pressure, BH1750 – light intensity) connected to an Arduino Uno development board equipped with the Atmega328 microcontroller, using digital and analog pins. The display of information is done on a monochrome screen attached to the Arduino board. The developed weather station is capable of measuring these four environmental parameters and providing readings at 5-minute intervals. Weather stations can be used in a variety of locations and domains from meteorology and weather monitoring, to agriculture, scientific research, navigation and aviation, or renewable energy industry. The weather stations can provide useful information on different weather parameters which is essential for providing accurate weather forecasts and monitoring climate changes, for optimizing the performance of energy installations and forecasting energy production.

The purpose of this paper is the design and realization of a prototype system for tracking the position of the sun, with two axes of rotation. The operating principle of the device is based on changing the position of the photovoltaic modules in the direction of the sun's rays, which maximizes the production of electricity. Solar panels with automatic adjustment according to the position of the sun are an innovative solution for optimizing the use of the solar energy. The promotion and use of solar energy is essential in our efforts to protect the planet and ensure a sustainable future.

For any person, company or institution, to secure goods, data, information, different methods were sought and thus the idea of access control appeared. Access control can be done by mobile phone, PIN code, access cards and, perhaps, the most secure way, the biometric feature. Once this idea appeared, it was also desired to automate access, in addition to securing it, and thus, the concept of an access control system appeared. These systems are used on a large scale, both in the public and in the private sector, because they ensure the improvement of the level of protection. This work aims to present a fingerprint-based access control system and the steps that are the basis of its implementation, starting from the block diagram, the functional specifications, the electrical diagram and up to the improvements made to the microcontroller program in the system component.

Artificial lift techniques are used when reservoir pressure drops below the fluid hydrostatic column weight in the well. A compressor station supplies high-pressure gas for the gas lift system, which includes a gas distribution manifold, gas lift lines to the well heads, and gas lift valves. Gas lift has many benefits, but the source of gas and the number of compression stages needed to lift reservoir fluid to the surface are major drawbacks. This paper critically examined this drawback and found a steady source of high-pressure gas that eliminates the need for compression. This study used PROSPER to determine the depths at which gas lift valves will be installed, the maximum gas injection rate of 0.81761 MMscf/day, the maximum oil production rate of 1183.4 STB/D, and the best valve type. Although the extra-high pressure gas (XHP) gas pressure needed to be reduced to properly aerate the fluid hydrostatic column as the gas lift valves (GLVs) opens, this pressure reduction (gas expansion) caused gas cooling/freezing, which is a critical concern on the lift gas path. Therefore, a heat exchanger and water bathe heater preheated the XHP gas to reduce the J-T phenomenon and ensure flow.