Search results for: deep injection well

Authors: Chun Pao Kuo, Chi Tong Lin

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The study explored atomization characteristics of tire pyrolysis fuel and its impacts on using three types of fuel: diesel oil mixed with 10% of tire pyrolysis fuel (called T10), diesel oil mixed with 20% tire pyrolysis (called T20), and consumer-grade diesel oil (D100). The investigators used the fuel for simulation and tests at various fuel injection timing, engine speed, and fuel injection speed to inspect impacts from fuel type on oil droplet atomization speed and output power. Actual vehicle tests were conducted using a 5-ton sedan (Hino) with 3660 cc displacement and a front-end inline four-cylinder diesel engine, and this type of vehicle is easily available from the market. A dynamometer was used to set up three engine speeds for the dynamometer testing at different injection timing and pressure. Next, an exhaust analyzer was used to measure exhaust pollution at different conditions to explore the effect of fuel types and injection speeds on output power in order to establish the best operation conditions for tire pyrolysis fuel.

Keywords: diesel engine, exhaust pollution, fuel injection timing, tire pyrolysis oil

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Authors: Joseph C. Chen, Venkata Karthik Jakka

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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: injection molding processes, taguchi parameter design, tensile strength, high-density polyethylene(HDPE)

Procedia PDF Downloads 177

Authors: M. Yousefi, N. Nasirzadeh

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In this paper, behavior of an oscillator under injection of another signal has been investigated. Also, variation of output signal amplitude versus injected signal phase variation, the effect of varying the amplitude of injected signal and quality factor of the oscillator has been investigated. The results show that the locking time depends on phase and the best locking time happens at 180-degrees phase. Also, the effect of injected lock has been discussed. Simulations show that the locking time decreases with signal injection to bulk. Locking time has been investigated versus various phase differences. The effect of phase and amplitude changes on locking time of a typical LC oscillator in 180 nm technology has been investigated.

Keywords: analysis, oscillator, injection-lock oscillator, phase modulation

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Alireza Moghtaderi, Negin Khakpour

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Hallux Valgus is a kind of Toes aberration where the Metatarsophalangeal joint that connects the big toe to the foot, leading to the inner side and a protrusion on the inner surface of toe arise. This study aimed to determine the effect of botulinum toxin A injection to reduce pain and deviation angle of the thumb in Hallux Valgus and to increase outcomes of treatment as an adjuvant therapy. Randomized clinical study was performed on 18 patients at the Clinic of Physical Medicine and Rehabilitation, Isfahan University of Medical Sciences. In this study the Halgvs valgus angle (HVA) between the metatarsals (IMA) and cartilage distal metatarsal angle (DMAA) and pain were assessed before and after injection. Average of Hallux Valgus angle before and after Botox injections were 28/89 ± 10/21 and 21/56 ± 8/22 degrees and the angle deviation in the 6 months after treatment was significantly improved (p <0.001). Injection of botulinum toxin A is a suitable and acceptable method to reform the skeleton deformities and also to reduce the pain in patients with Hallux valgus.

Keywords: metatasal, hallux valgus, pain, botulinum toxuin

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Authors: Alan C. Lin, Ricky N. Joevan

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This paper focuses on developing a system to transfer mold base plates and standard parts faster during the stage of injection mold design. This system not only provides a way to compare the file version, but also it utilizes Siemens NX 10 to isolate the updated information into a single executable file (.dll), and then, the file can be transferred without the need of transferring the whole file. By this way, the system can help the user to download only necessary mold base plates and standard parts, and those parts downloaded are only the updated portions.

Keywords: CAD, injection molding, mold base, data retrieval

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: Erdem Elibol, Musa Cadırcı, Nedim Tutkun

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Recently, colloidal quantum dots (CQDs) have drawn increasing attention due to their unique size tunability, which makes them potential candidates for numerous applications including photovoltaic, LEDs, and imaging. However, the main challenge to exploit CQDs properly is that there has not been an effective method to produce them with highly crystalline form and narrow size dispersion. Hot injection method is one of the widely used techniques to produce high-quality nanoparticles. In this method, the key parameter is to reduce the time for injection of the precursors into each other, which yields fast and constant nucleation rate and hence to highly monodisperse QDs. In conventional hot injection method, the injection of precursors is carried out using standard lab syringes with long needles. However, this technique is relatively slow and thus will result in poor optical properties in QDs. In this work, highly luminescent CdTe QDs were synthesised by transferring hot precursors into each other using cannula method. Unlike regular syringe technique, with the help of high pressure difference between two precursors’ flasks and wide cross-section of cannula, the hot cannulation process is too short which yields narrow size distribution and high quantum yield of CdTe QDs. Here QDs with full width half maximum (FWHM) of 28 nm was achieved. In addition, the photoluminescence quantum yield of our samples was measured to be about 21 ± 0.9 which is at least twice the previous record values for CdTe QDs wherein syringe was used to transfer precursors.

Keywords: CdTe, hot injection method, luminescent, quantum dots

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Authors: Tadashi Watanabe

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The LSTF experiment simulating the SGTR accident at the Mihama Unit-2 reactor is analyzed using the RELAP5/MOD3.3 code. In the accident and thus in the experiment, the ECC water was injected not only into the cold legs but into the upper plenum. Overall transients during the experiment such as pressures and fluid temperatures are simulated well by the code. The cold-leg fluid temperatures are shown to decrease if the upper plenum injection system is connected to the cold leg. It is found that the cold-leg fluid temperatures also decrease if the upper-plenum injection is not used and the cold-leg injection alone is actuated.

Keywords: SGTR, LSTF, RELAP5, ECCS

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Authors: Seyed Mostafa Jafari Raad, Hassan Hassanzadeh

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Injection of impurities along with CO₂ into saline aquifers provides an exceptional prospect for low-cost carbon capture and storage technologies and can potentially accelerate large-scale implementation of geological storage of CO₂. We have conducted linear stability analyses and numerical simulations to investigate the effects of permitted impurities in CO₂ streams on the onset of natural convection and dynamics of subsequent convective mixing. We have shown that the rate of dissolution of an impure CO₂ stream with H₂S highly depends on the operating conditions such as temperature, pressure, and composition of impurity. Contrary to findings of previous studies, our results show that an impurity such as H₂S can potentially reduce the onset time of natural convection and can accelerate the subsequent convective mixing. However, at the later times, the rate of convective dissolution is adversely affected by the impurities. Therefore, the injection of an impure CO₂ stream can be engineered to improve the rate of dissolution of CO₂, which leads to higher storage security and efficiency. Accordingly, we have identified the most favorable CO₂ stream compositions based on the geophysical properties of target aquifers. Information related to the onset of natural convection such as the scaling relations and the most favorable operating conditions for CO₂ storage developed in this study are important in proper design, site screening, characterization and safety of geological storage. This information can be used to either identify future geological candidates for acid gas disposal or reviewing the current operating conditions of licensed injection sites.

Keywords: CO₂ storage, solubility trapping, convective dissolution, storage efficiency

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Mohaya Farzin, Shahin Hassanpour, Morteza Zendehdel, Bita Vazir, Ahmad Asghari

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Aim: There are several differences between birds and mammals in terms of food intake regulation. Therefore, this study aimed to investigate the effects of the intracerebroventricular (ICV) injection of spexin and its interaction with nitric oxide, serotonin, and corticotropin receptors on central food intake regulation in broiler chickens. Materials and Methods: In experiment 1, chickens received ICV injection of saline, PCPA (p-chlorophenyl alanine,1.25 µg), spexin, and PCPA+spexin. In experiments 2-7, 8-OH-DPAT (5-HT1A agonist, 15.25 nmol), SB-242084 (5-HT2C receptor antagonist, 1.5µg), L-arginine (Precursor of nitric oxide, 200 nmol), L-NAME (nitric oxide synthetase inhibitor, 100 nmol), Astressin-B (CRF1/CRF2 receptor antagonist, 30 µg) and Astressin2-B (CRF2 receptor antagonist, 30 µg) were injected to chickens instead of the PCPA. Then, food intake was measured until 120 minutes after the injection. Results: Spexin significantly decreased food consumption (P<0.05). Concomitant injection of SB-242084+spexin attenuated spexin-induced hypophagia (P<0.05). Co-injection of L-arginine+spexin enhanced spexin-induced hypophagia, and this effect was reversed by L-NAME (P<0.05). Also, concomitant injection of Astressin-B + spexin or Astressin2-B + spexin enhanced spexin-induced hypophagia (P<0.05). Conclusions: Based on these observations, spexin-induced hypophagia may be mediated by nitric oxide and 5-HT2C, CRF1, and CRF2 receptors in neonatal broiler chickens.

Keywords: spexin, serotonin, corticotropin, nitric oxide, food intake, chicken

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Authors: M. Abdallah

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Urban development requires deep excavations near buildings and other structures. Deep excavation has become more a necessity for better utilization of space as the population of the world has dramatically increased. In Lebanon, some urban areas are very crowded and lack spaces for new buildings and underground projects, which makes the usage of underground space indispensable. In this paper, a numerical modeling is performed using the finite element method to study the deep excavation-diaphragm wall soil-structure interaction in the case of nonlinear soil behavior. The study is focused on a comparison of the results obtained using different support systems. Furthermore, a parametric study is performed according to the remoteness of the structure.

Keywords: deep excavation, ground anchors, interaction soil-structure, struts

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Authors: Jian Wang, Lu Yang, Jiong Peng

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Internal circulation two-platen clamping system for injection molding machine (IMM) has many potential advantages on energy-saving. In order to estimate its properties, experiments in this paper were carried out. Displacement and pressure of the components were measured. In comparison, the model of hydraulic clamping system was established by using AMESim. The related parameters as well as the energy consumption could be calculated. According to the analysis, the hydraulic system was optimized in order to reduce the energy consumption.

Keywords: AMESim, energy-saving, injection molding machine, internal circulation

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Armin Najipour, A. M. Fattahi

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The aim of this research was to investigate the effect of the addition of multi walled carbon nanotubes on the mechanical properties of polyethylene/carbon nanotube nanocomposites. To do so, polyethylene and carbon nanotube were mixed in different weight percentages containing 0, 0.5, 1, and 1.5% carbon nanotube in two screw extruder apparatus by fusion. Then the nanocomposite samples were molded in injection apparatus according to ASTM: D6110 standard. The effects of carbon nanotube addition in 4 different levels and injection pressure in 2 levels on the hardness and impact strength of the nanocomposite samples were investigated. The results showed that the addition of carbon nanotube had a significant effect on improving hardness and impact strength of the nanocomposite samples such that by adding 1% w/w carbon nanotube, the impact strength and hardness of the samples improved to 74% and 46.7% respectively. Also, according to the results, the effect of injection pressure on the results was much less than that of carbon nanotube weight percentage.

Keywords: carbon nanotube, injection molding, mechanical properties, nanocomposite, polyethylene

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Authors: Muluneh Ademe, Zeleke Mekonnen

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Objective: to determine the level of bacterial contamination of reused insulin syringes among diabetic patients. Method: A facility based cross-sectional study was conducted among diabetic patients. Data on socio-demographic variables, history of injection syringe reuse, and frequency of reuse of syringes were collected using predesigned questionnaire. Finally, the samples from the syringes were cultured according to standard microbiological techniques. Result: Eighteen diabetic patients at Jimma University Hospital participated. A total of 83.3% of participants reused a single injection syringe for >30 consecutive injections, while 16.7% reused for >30 injections. Our results showed 22.2% of syringes were contaminated with methicillin-resistant Staphylococcus aures. Conclusion: We conclude reuse of syringe is associated with microbial contamination. The findings that 4/18 syringes being contaminated with bacteria is an alarming situation. A mechanism should be designed for patients to get injection syringes with affordable price. If reusing is not avoidable, reducing number of injections per a single syringe and avoiding needle touching with hand or other non-sterile material may be an alternative to reduce the risk of contamination.

Keywords: diabetes mellitus, Ethiopia, subcutaneous insulin injection, syringe reuse

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Authors: M. Dezyani, R. Ezzati, H. Mirzaei

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The objectives of this study were to determine the effect of pH on chemical, structural, and functional properties of Fetta cheese, and to relate changes in structure to changes in cheese unctionality. Fetta cheese was obtained from a cheese-production facility and stored at 4°C. Ten days after manufacture, the cheese was cut into blocks that were vacuum-packaged and stored for 4 d at 4°C. Cheese blocks were then high-pressure injected one, three, or five times with a 20% (wt/wt) glucono-δ-lactone solution. Successive injections were performed 24 h apart. Cheese blocks were then analyzed after 40 d of storage at 4°C. Acidulant injection decreased cheese pH from 5.3 in the uninjected cheese to 4.7 after five injections. Decreased pH increased the content of soluble calcium and slightly decreased the total calcium content of cheese. At the highest level, injection of acidulant promoted syneresis. Thus, after five injections, the moisture content of cheese decreased from 34 to 31%, which esulted in decreased cheese weight. Lowered cheese pH, 4.7 compared with 5.3, also resulted in contraction of the protein matrix. Acidulant injection decreased cheese hardness and cohesiveness, and the cheese became more crumbly.

Keywords: calcium, high-pressure injection, protein matrix, syneresis

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Authors: Mehdi Tavana, Seyedeh Zeinab Peighambarzadeh

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Pyelography is used for morphologic and especially functional studies of the urinary tracts. There are many indications for excretory Pyelography in humans and animals. Intravenous Pyelography is the most practical method; other Pyelography techniques were manipulated because of difficulties for finding veins in small size of the patients. At the best of times, the combination of small veins and abundant subcutaneous tissue makes vascular access difficult or impossible, therefore, another methods of administration of contrast media is desired. This study was performed to evaluate the feasibility of intraosseous injection of iodixanol in providing a safe and diagnostic urogram in Persian squirrel. Fourteen hundred mg iodine per kilogram body weight of iodixanol was injected subcutaneously over tibial tuberosity on ten clinically healthy adult Persian squirrels with no signs of urinary system disorder. Lateral and ventrodorsal radiographs were taken every 2 minutes until the pyelogram was finished. Intraosseous injection of iodixanol was successful to show nephrogram, pyelogram, uretrogram and cystogram clearly. There were no abnormal clinical signs after one week of experiments. Biochemical and hematological profiles were in normal ranges. It is concluded that intraosseous Pyelography is an effective and reliable method for Pyelography studies in squirrel. Microscopic examinations of the kidneys and the site of injection after one week were normal.

Keywords: pyelography, intraosseous injection, iodixanol, persian squirrel

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Authors: Amin Adeli, Maryam Zarei

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Background and purpose: Royal jelly (RJ) is a natural product with anti-hyperlipidemic and antioxidant properties. In ovo administration of RJ may improve lipid profile and antioxidant properties. This study was conducted to evaluate, for first time, the effects of in ovo injection of the RJ on hatchability, one-day old chick quality, total antioxidant status and blood lipoproteins. Methods: 400 incubating eggs produced by Ross 308 strain (52 weeks of age in first stage of production) were prepared and assigned into 4 groups (n=100) and 4 replications per group (n=25). These 4 groups were injected by the following pattern: 1) 0.1 ml normal saline (control), 2) 0.1 mg RJ+0.1 ml normal saline, 3) 0.2 mg RJ+0.1 ml normal saline, and 4) 0.3 mg RJ+0.1 ml normal saline. Injections were performed using a laminar flow system Lipid profile, antioxidant properties, hatchability, and one-day old chicken quality were assessed. Results: The administration of RJ at concentration of 0.1increased the percentage of hatchability compared to concentration of 0.2 and control, significant differences have not been observed among groups for quality scores (P>0.05). The results showed that in ovo injection of the RJ did not have any significant effects on lipid profile; but administration of the RJ only decreased High-density lipoprotein (HDL cholesterol, HDL-C) (P<0.05). The results showed that injection of the RJ at concentration of 0.3 increased total antioxidant capacity (TAC) compared to control group (p<0.05). Injection of the RJ progressively increased gluthation peroxidase (GPx) activity (p<0.05). The results showed that injection of the RJ decreased superoxide dismutase (SOD) compared to control group (p<0.05). Conclusion: In ovo injection of the RJ at the highest concentration increased TAC and GPx, but it did not have significant effects on lipid profile. Future studies are needed to investigate the effects of the RJ on the above-mentioned mechanisms.

Keywords: antioxidant enzymes, chicken quality, hatchability, royal jelly

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Weiyao Zhu, Bingbing Li, Yajing Liu, Zhiyong Song

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Branched-preformed particle gel (B-PPG) is a newly developed profile control and oil displacement agent for enhanced oil recovery in major oilfields. To provide a better understanding of the performance of B-PPG in high temperature reservoirs, a comprehensive experimental investigation was conducted by utilizing glass micromodel and synthetic core. The microscopic experimental results show that the B-PPG can selectively flow and plug in large pores. In terms of enhanced oil recovery, the decrease of residual oil in the margin regions (24.6%) was higher than that in the main stream (13.7%), which indicates it enlarged the sweep area. In addition, the effects of B-PPG injection concentration and injection rate on enhanced oil recovery were implemented by core flooding. The macroscopic experimental results indicate that the enhanced oil recovery increased with the increasing of injection concentration. However, the injection rate had a peak value. It is significant to get insight into the behaviors of B-PPG in reservoirs.

Keywords: branched-preformed particle gel, enhanced oil recovery, micromodel, core flooding

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Authors: Shota Nagata, Kazuya Okubo, Toru Fujii

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The purpose of this study is to investigate the proper condition in extracting carbon fibers as the reinforcement of composite molded by injection method. Recycled carbon fibers were extracted from wasted CFRP by pyrolyzing epoxy matrix of CFRP under air atmosphere at different temperature conditions 400, 600 and 800°C in this study. Recycled carbon fiber reinforced polypropylene (RCF/PP) pellets were prepared using twin screw extruder. The RCF/PP specimens were molded into dumbbell shaped specimens using injection molding machine. The tensile strength of recycled carbon fiber was decreased with rising pyrolysis temperature from 400 to 800°C. However, superior mechanical properties of tensile strength, tensile modulus and fracture strain of RCF/PP specimen were obtained when the extracting temperature was 600°C. Almost fibers in RCF/PP specimens were aligned in the mold filling direction in this study when the extracting temperature was 600°C. To discuss the results, the failure mechanisms of RCF/PP specimens was shown schematically. Finally, it was concluded that the temperature condition at 600°C should be selected in extracting carbon fibers as the reinforcement of RCF/PP composite molded by injection method.

Keywords: CFRP, recycled carbon fiber, injection molding, mechanical properties, fiber orientation, failure mechanism

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Authors: Mannal Tariq

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Construction industry is making progress at a high pace. The trend of the world is getting more biased towards the high rise buildings. Deep beams are one of the most common elements in modern construction having small span to depth ratio. Deep beams are mostly used as transfer girders. This experimental study consists of 16 reinforced concrete (RC) deep beams. These beams were divided into two groups; A and B. Groups A and B consist of eight beams each, having 381 mm (15 in) and 457 mm (18 in) depth respectively. Each group was further subdivided into four sub groups each consisting of two identical beams. Each subgroup was comprised of solid/control beam (without opening), opening above neutral axis (NA), at NA and below NA. Except for control beams, all beams with openings were strengthened with carbon fibre reinforced polymer (CFRP) vertical strips. These eight groups differ from each other based on depth and location of openings. For testing sake, all beams have been loaded with two symmetrical point loads. All beams have been designed based on strut and tie model concept. The outcome of experimental investigation elaborates the difference in the shear behaviour of deep beams based on depth and location of circular openings variation. 457 mm (18 in) deep beam with openings above NA show the highest strength and 381 mm (15 in) deep beam with openings below NA show the least strength. CFRP sheets played a vital role in increasing the shear capacity of beams.

Keywords: CFRP, deep beams, openings in deep beams, strut and tie modal, shear behaviour

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Authors: Genaro Bolívar, Manuel Mas, Maria Tortolero, Jorge Salazar

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Due to the extensive use of water injection for oil displacement and pressure maintenance in oil fields, many reservoirs experience the problem of scale deposition when injection water starts to break through. In most cases the scaled-up wells are caused by the formation of sulfate and carbonate scales of calcium and strontium. Due to their relative hardness and low solubility, there are limited processes available for their removal and preventive measures such as the “squeeze” inhibitor treatment have to be taken. It is, therefore, important to gain a proper understanding of the kinetics of scale formation and its detrimental effects on formation damage under both inhibited and uninhibited conditions. Recently, the production of chitosan was started in our country and in the PDVSA-Intevep laboratories was synthesized and evaluated the properties of carboxymethyl chitosan (CMQ) as chelating agent of Ca2 + ions in water injection. In this regard, the characterization of the biopolymer by 13C - NMR, FTIR, TGA, and TM0374-2007 standard laboratory test has demonstrated the ability to remove up to 70% calcium ions in solution and shows a behavior that approaches that of commercial products.

Keywords: carboxymethyl chitosan, scale, calcium carbonate scale deposition, water injection

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Embankment settlement on soft clays has always been problematic due to the high compaction and low shear strength of the soil. Deep soil mixing and geosynthetics are two soil improvement methods in such fields. Here, a numerical study is conducted on the embankment performance on the soft ground improved by deep soil mixing columns and geosynthetics based on the data of a real project. For this purpose, the finite element method is used in the Plaxis 2D software. The Soft Soil Creep model considers the creep phenomenon in the soft clay layer while the Mohr-Columb model simulates other soil layers. Results are verified using the data of an experimental embankment built on deep mixing columns. The effect of depth and diameter of deep mixing columns and the stiffness of geogrid on the vertical and horizontal movements of embankment on clay subsoil will be investigated in the following.

Keywords: PLAXIS 2D, embankment settlement, horizontal movement, deep soil mixing column, geogrid

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Mohamed Hassan, Rahul Gajbhiye

Abstract:

The high mobility and gravity override of CO₂ gas can be minimized by generating the CO₂ foam with the aid of surfactant. However, CO₂ is unable to generate the foam/stable foam above its supercritical point (1100 psi, 31°C). These difficulties with CO₂ foam is overcome by adding N₂ in small fraction to enhance the foam generation of CO₂ at supercritical conditions. This study shows how the addition of small quantity of N₂ helps in generating the CO₂ foam and performance of the CO₂/N₂ mixture foam in enhanced oil recovery. To investigate the performance of CO₂/N₂ foam, core-flooding experiments were conducted at elevated pressure and temperature condition (higher than supercritical CO₂ - 50°C and 1500 psi) in sandstone cores. Fluorosurfactant (FS-51) was used as a foaming agent, and n-decane was used as model oil in all the experiments. The selection of foam quality and N₂ fraction was optimized based on foam generation and stability tests. Every gas or foam flooding was preceded by seawater injection to simulate the behavior in the reservoir. The results from the core-flood experiments showed that the CO₂ and CO₂/N₂ foam flooding recovered an additional 34-40% of Original Initial Oil in Place (OIIP) indicating that foam flooding succeeded in producing more oil than pure CO₂ gas injection processes. Additionally, the performance CO₂/N₂ foam injection was better than CO₂ foam injection.

Keywords: CO₂/N₂ foam, enhanced oil recovery (EOR), supercritical CO₂, sweep efficiency

Procedia PDF Downloads 263

Authors: Ruqaya H. Aljabery

Abstract:

Reinforced Concrete (RC) deep beams are one of the main critical structural elements in terms of safety since significant loads are carried in a short span. The shear capacity of these sections cannot be predicted accurately by the current design codes like ACI and EC2; thus, they must be investigated. In this research, non-linear behavior of RC deep beams strengthened in shear with Fiber Reinforced Polymer (FRP) strips, and the efficiency of FRP in terms of enhancing the shear capacity in RC deep beams are examined using Finite Element Analysis (FEA), which is conducted using the software ABAQUS. The effect of several parameters on the shear capacity of the RC deep beam are studied in this paper as well including the effect of the cross-sectional area of the FRP strip and the shear reinforcement area to the spacing ratio (As/S), and it was found that FRP enhances the shear capacity significantly and can be a substitution of steel stirrups resulting in a more economical design.

Keywords: Abaqus, concrete, deep beam, finite element analysis, FRP, shear strengthening, strut-and-tie

Procedia PDF Downloads 130