Investigation of the viable role of oil sludge-derived activated carbon for oily wastewater remediation

A wide range of studies has been carried out to describe the equilibrium data of adsorption for the surface adsorption process. However, no extensive investigation has been carried out to evaluate the oil sludge based activated carbon surface adsorption. Therefore, the possibility of carbon active production using different oil sludges and consequently the adsorption mechanism of these kind of adsorbents is still unknown. In this study, a novel low-cost approach was introduced to synthesize the activated carbon using oil sludge applying a two-step process including carbonization and chemical activation. In this way, four different types of oil sludges were characterized and then applied to synthesize different carbon actives and their performance were investigated as an adsorbent. The results showed that all synthesized activated carbons, with about 6% ash and pH = 7 and the specific surface area of 110 m2/gr, have the ability to treatment of oily wastewater; which can be referred to the high carbon content (>80%). The iodine number and the efficiency of prepared activated carbon were obtained as 406.8 mg/g and 94%, respectively. The adsorption process was also studied at different process conditions such as temperature (308–338 K), pH value (3–9) and adsorbent amount (50–200 mg/L) to find the optimum condition for wastewater treatment. The results show that the pH value has an optimum in the adsorption rate (the maximum adsorption was measured at pH = 5) and the adsorption capacity can be reduced by increasing the temperature or decreasing the adsorbent amount. Moreover, three different adsorption isotherm models were applied, i.e., Langmuir, Temkin, and Freundlich isotherms; which the Langmuir equation was more suitable than others investigated isotherm models with R2 ≈ 0.999

A novel investigation on finding optimal mode and performance improvement of a control system

According to the widespread advance in technological industry, there has been an essential need of high quality and speed methods for data transmission. In many field such as Electrical Engineering, Data Science, Computer Engineering, and Information and Communication Technology efficient transfer for acquired data are leaded to a great improvement in ultimate performance. Hence traditional way of transmitting data is strongly dependent on the distances among the devices; present work applies Frequency Control and First-order low-pass filtering control model to optimize data transmission. The trends of current results are in good agreement with previous literature. Then the relation between data transmission and output powers are discuss. After that, the effect of distance on data transformation for laboratory equipment is explained. Finally, it was observed that a vital way for resources management is controlling the way for data transformation

Розробка класифікатора аудіокоманд на основі мікрофону з використанням згорткової нейронної мережі

Audio command recognition methods are essential to be recognized for performing user instructions, especially for people with disabilities. Previous studies couldn’t examine and classify the performance optimization of up to twelve audio commands categories. This work develops a microphone-based audio commands classifier using a convolutional neural network (CNN) with performance optimization to categorize twelve classes including background noise and unknown words. The methodology mainly includes preparing the input audio commands for training, extracting features, and visualizing auditory spectrograms. Then a CNN-based classifier is developed and the trained architecture is evaluated. The work considers minimizing latency by optimizing the processing phase by compiling MATLAB code into C code if the processing phase reaches a peak algorithmically. In addition, the method conducts decreasing the frame size and increases the sample rate that is also contributed to minimizing latency and maximizing the performance of processing audio input data. A modest bit of dropout to the input to the final fully connected layer is added to lessen the likelihood that the network will memorize particular elements of the training data. We explored expanding the network depth by including convolutional identical elements, ReLu, and batch normalization layers to improve the network's accuracy. The training progress demonstrated how fast the accuracy of the network is increasing to reach about 98.1 %, which interprets the ability of the network to over-fit the data of training. This work is essential to serve speech and speaker recognition such as smart homes and smart wheelchairs, especially for people with disabilitiesМетоди розпізнавання звукових команд є важливими для виконання інструкцій користувача, особливо для людей з обмеженими можливостями. Попередні дослідження не змогли дослідити та класифікувати оптимізацію продуктивності до дванадцяти категорій аудіокоманд. Ця робота розробляє класифікатор звукових команд на основі мікрофона з використанням згорткової нейронної мережі (ЗНМ) з оптимізацією продуктивності для класифікації дванадцяти класів, включаючи фоновий шум і невідомі слова. Методологія в основному включає підготовку вхідних аудіокоманд для навчання, виділення функцій і візуалізацію слухових спектрограм. Потім розробляється класифікатор на основі ЗНМ і оцінюється навчена архітектура. У роботі розглядається мінімізація затримки шляхом оптимізації фази обробки шляхом компіляції коду MATLAB у код C, якщо фаза обробки алгоритмічно досягає піку. Крім того, метод зменшує розмір кадру та збільшує частоту дискретизації, що також сприяє мінімізації затримки та максимізації продуктивності обробки вхідних аудіоданих. До вхідних даних остаточного повністю підключеного рівня додається невеликий викид, щоб зменшити ймовірність того, що мережа запам’ятає певні елементи навчальних даних. Ми досліджували можливість розширення глибини мережі за допомогою згорткових ідентичних елементів, ReLu та шарів пакетної нормалізації для підвищення точності мережі. Прогрес навчання продемонстрував, як швидко зростає точність мережі, досягнувши приблизно 98,1 %, що пояснює здатність мережі перевищувати дані навчання. Ця робота є важливою для розпізнавання мовлення та мовців, таких як розумні будинки та розумні інвалідні візки, особливо для людей з обмеженими можливостям

Wastewater Management Using Coagulation and Surface Adsorption through Different Polyferrics in the Presence of TiO₂-g-PMAA Particles

For the surface adsorption process, a wide range of studies have been carried out to describe the adsorption process. However, no extensive study has been carried out to investigate the pre-treatment method effect on the separation process. The purpose of the present study is to improve the performance of the membrane process in the treatment of oily wastewater. For this purpose, the effects of pre-treatment, membrane modification, and operational parameters were investigated on the microfiltration membrane system. Two methods of coagulation and surface adsorption were used as pre-treatment, and then a modified polysulfone (PSf) membrane containing TiO2 nanoparticles was applied in the microfiltration process. In order to reduce the membrane fouling and increase the permeate flux, the surface of the nanoparticle was modified. In order to check the performance of coagulation, pretreatments of polyferric sulfate (PFS) and polyferric chloride (PFC) were applied. The results showed that the Chemical Oxygen Demand (COD) reduction of 98% can be obtained using 1 g/L of PFS coagulant at pH = 6, while only 81% of COD was removed using 1 g/L PFC. It was also found that the best pH for the performance of this type of coagulant was measured as pH = 10 and the removal efficiency for 1 and 2 g/L of PFC coagulant was obtained as 96.1% and 91.7%, respectively. The results show that in the case of using a coagulant of less than 1 g/L, using PFS is more efficient than PFC; meanwhile, in more than 1 g/L of coagulant, this effect is reversed and the use of PFS will be less efficient than PFC. The performance of the PSf-TiO2 membrane fabricated by the Nonsolvent-induced phase separation (NIPS) method was investigated using modified nanoparticles with an initial size of 10 nm at different operating conditions. The results show that the permeate flux and the rejection can be increased to 563 L/h m2 and 99%, respectively, using the modified PSf membrane. The results of this paper showed that the performance of the adsorption process can be improved by using the coagulation process as a pre-treatment method

Investigation of the viable role of oil sludge-derived activated carbon for oily wastewater remediation

A wide range of studies has been carried out to describe the equilibrium data of adsorption for the surface adsorption process. However, no extensive investigation has been carried out to evaluate the oil sludge based activated carbon surface adsorption. Therefore, the possibility of carbon active production using different oil sludges and consequently the adsorption mechanism of these kind of adsorbents is still unknown. In this study, a novel low-cost approach was introduced to synthesize the activated carbon using oil sludge applying a two-step process including carbonization and chemical activation. In this way, four different types of oil sludges were characterized and then applied to synthesize different carbon actives and their performance were investigated as an adsorbent. The results showed that all synthesized activated carbons, with about 6% ash and pH = 7 and the specific surface area of 110 m2/gr, have the ability to treatment of oily wastewater; which can be referred to the high carbon content (&gt;80%). The iodine number and the efficiency of prepared activated carbon were obtained as 406.8 mg/g and 94%, respectively. The adsorption process was also studied at different process conditions such as temperature (308–338 K), pH value (3–9) and adsorbent amount (50–200 mg/L) to find the optimum condition for wastewater treatment. The results show that the pH value has an optimum in the adsorption rate (the maximum adsorption was measured at pH = 5) and the adsorption capacity can be reduced by increasing the temperature or decreasing the adsorbent amount. Moreover, three different adsorption isotherm models were applied, i.e., Langmuir, Temkin, and Freundlich isotherms; which the Langmuir equation was more suitable than others investigated isotherm models with R2 ≈ 0.999.Validerad;2023;Nivå 2;2023-02-24 (joosat);Funder:  King Khalid University (RGP.2/182/43)Licens fulltext: CC BY License</p

Thermodynamic and structural investigation of oily wastewater treatment using peach kernel and walnut shell based activated carbon.

Despite the many articles about activated carbon with different precursors in adsorption process, no in-depth research has been carried out to understand the causes of the difference in surface adsorption characteristics of activated carbon with different precursors and different activation processes. In this work, the ability of two active carbon adsorbents made of walnut shell and peach kernel by two chemical and physical methods (totally 4 different types of activated carbon) in treatment of oily wastewater including diesel, gasoline, used oil or engine lubricant has been compared. The results show that the chemical activated peach carbon active with 97% hardness has provided the highest hardness and physical activated walnut carbon active has obtained the lowest hardness value (87%). It is also found that peach activated carbon has a higher iodine number than walnut activated carbon, and this amount can be increased using chemical methods; Therefore, the highest amount of Iodine Number is related to Peach activated carbon that is made by chemical method (1230 mg/g), and the lowest amount of iodine number is seen in walnut activated carbon that is made by physical method (1020 mg/g). moreover, the pore diameter of physical activated carbon is lower than chemical activated carbon in all cases. So that the pore diameter of chemical activated peach carbon active is equal to 22.08 μm and the measured pore diameter of physical activated peach carbon active is equal to 20.42 μm. These values for walnut are obtained as 22.74 μm and 21.86 μm, respectively. Furthermore, the temperature and pH effects on the adsorption of different synthesized oily wastewater was studied and it was found that a decrease in adsorption can be seen with an increase in temperature or decreasing the pH value, which can be referred to this fact that the process of adsorption is an exothermic process. Finally, to analyze the compatibility of adsorption isotherms with experimental data and to predict the adsorption process, three different isotherms named Langmuir, Temkin, and Freundlich isotherms were applied and their parameters were correlated. The correlation results show that the Langmuir isotherm had the best correlation in all cases compared to the Freundlich and Temkin isotherms, based on the correlation coefficient, and the calculated R2 values which was greater than 0.99 in all the studied cases

The novelty of using the AGM and FEM for solutions of partial differential and ordinary equations along a stretchable straight cylinder

Near the suction/injection area, a scientific definition for laminar boundary layer flow and heat transfer of an incompressible viscous flow over a stretching cylinder is given. In the study, differential equations with partial derivatives are converted into dimensionless coupled equations using numerical and analytical methods of Akbari- Ganji and Finite Elements Methods. The goal of this first stage of research and research on this topic is to use simplified forms to simplify equations using derivatives of simplified forms; the analysis of the displacement of the heat flux and the velocity gradient will be done using the changes of the Prandtl number. Based on the results obtained on this issue, it is found that the suction process increments surface firmness and quality, whereas the injection decreases surface skin friction. Also, at the points where the water and oil are attached to the surface of the cylinder, the heat has reached its maximum value, and as the distance increases along the Y axis, the temperature decreases. The highest temperature gradient is observed for water fluid. This shows that the use of water fluid around the cylinder accelerates the process of heat transfer from the surface to the outside of the boundary layer. One of the differences between the use of oil and water fluid around the cylinder according to the 2D contours is the difference in the temperature gradient of the two fluids. So that the highest temperature gradient is observed for water fluid

Thermodynamic and structural investigation of oily wastewater treatment using peach kernel and walnut shell based activated carbon

Despite the many articles about activated carbon with different precursors in adsorption process, no in-depth research has been carried out to understand the causes of the difference in surface adsorption characteristics of activated carbon with different precursors and different activation processes. In this work, the ability of two active carbon adsorbents made of walnut shell and peach kernel by two chemical and physical methods (totally 4 different types of activated carbon) in treatment of oily wastewater including diesel, gasoline, used oil or engine lubricant has been compared. The results show that the chemical activated peach carbon active with 97% hardness has provided the highest hardness and physical activated walnut carbon active has obtained the lowest hardness value (87%). It is also found that peach activated carbon has a higher iodine number than walnut activated carbon, and this amount can be increased using chemical methods; Therefore, the highest amount of Iodine Number is related to Peach activated carbon that is made by chemical method (1230 mg/g), and the lowest amount of iodine number is seen in walnut activated carbon that is made by physical method (1020 mg/g). moreover, the pore diameter of physical activated carbon is lower than chemical activated carbon in all cases. So that the pore diameter of chemical activated peach carbon active is equal to 22.08 μm and the measured pore diameter of physical activated peach carbon active is equal to 20.42 μm. These values for walnut are obtained as 22.74 μm and 21.86 μm, respectively. Furthermore, the temperature and pH effects on the adsorption of different synthesized oily wastewater was studied and it was found that a decrease in adsorption can be seen with an increase in temperature or decreasing the pH value, which can be referred to this fact that the process of adsorption is an exothermic process. Finally, to analyze the compatibility of adsorption isotherms with experimental data and to predict the adsorption process, three different isotherms named Langmuir, Temkin, and Freundlich isotherms were applied and their parameters were correlated. The correlation results show that the Langmuir isotherm had the best correlation in all cases compared to the Freundlich and Temkin isotherms, based on the correlation coefficient, and the calculated R2 values which was greater than 0.99 in all the studied cases

Numerical investigation of the effect of changes in blood viscosity on parameters hemodynamic blood flow in the left coronary artery with consideration capturing fluid–solid interaction

Cardiovascular diseases are unfortunately one of the leading causes of death in today's society. It is important to analyze blood flow in various parts of the circulatory system. The coronary artery is made up of four main arteries, and the left coronary artery is responsible for delivering blood to the heart muscle. This research utilizes computational fluid dynamics and finite element methods to investigate and analyze coronary vessels by studying changes in blood characteristics. The aim of this study is to analyze and model the flow of blood under different conditions of the coronary vessels, with a particular focus on the vessels on the left side. This is in response to changes in hematocrit, which can cause an increase or decrease in blood viscosity (μp) (N.s/m2). In general, by applying condition flexibility for the vessel, it is possible to reduce pressure distribution on the wall when compared to the rigid model. When considering changes in viscosity (μ) (kg/m. s), such as an increase from 0.0029 to 0.0067, this can lead to changes in the shear stress distribution (N/m2) on the wall. Specifically, this increase in blood viscosity (μp) (N.s/m2) causes maximum tension, resulting in the wall shear WSS (N/m2) rising from 60 to 154 Pascal's, which is a 140% increase. Based on the current data, it appears that there is a high flow pressure in the artery, resulting in maximum relative pressure values of 6300 and 6450 Pascal's for the rigid and flexible models, respectively, at the separating joint of the bifurcation

Optimization of oil industry wastewater treatment system and proposing empirical correlations for chemical oxygen demand removal using electrocoagulation and predicting the system’s performance by artificial neural network

The alarming pace of environmental degradation necessitates the treatment of wastewater from the oil industry in order to ensure the long-term sustainability of human civilization. Electrocoagulation has emerged as a promising method for optimizing the removal of chemical oxygen demand (COD) from wastewater obtained from oil refineries. Therefore, in this study, electrocoagulation was experimentally investigated, and a single-factorial approach was employed to identify the optimal conditions, taking into account various parameters such as current density, pH, COD concentration, electrode surface area, and NaCl concentration. The experimental findings revealed that the most favorable conditions for COD removal were determined to be 24 mA/cm2 for current density, pH 8, a COD concentration of 500 mg/l, an electrode surface area of 25.26 cm2, and a NaCl concentration of 0.5 g/l. Correlation equations were proposed to describe the relationship between COD removal and the aforementioned parameters, and double-factorial models were examined to analyze the impact of COD removal over time. The most favorable outcomes were observed after a reaction time of 20 min. Furthermore, an artificial neural network model was developed based on the experimental data to predict COD removal from wastewater generated by the oil industry. The model exhibited a mean absolute error (MAE) of 1.12% and a coefficient of determination (R2) of 0.99, indicating its high accuracy. These findings suggest that machine learning-based models have the potential to effectively predict COD removal and may even serve as viable alternatives to traditional experimental and numerical techniques.Validerad;2023;Nivå 2;2023-09-26 (sofila);Funder: King Khalid UniversityAbha, Saudi Arabia (Grant no. RGP. 2/57/44)</p