Search results for: tuning of process parameters

Authors: Shativel S., Chandana B. R., Kavya B. C., Obli B. Vikram, Suganthi J., Nagendra Rao G.

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Satellite communication plays a pivotal role in modern global communication networks, serving as a vital link between terrestrial infrastructure and remote regions. The demand for reliable satellite reception systems, especially in UHF (Ultra High Frequency) and VHF (Very High Frequency) bands, has grown significantly over the years. This research paper presents the design and optimization of a high-gain, dual-band crossed Yagi-Uda antenna in CST Studio Suite, specifically tailored for satellite reception. The proposed antenna system incorporates a circularly polarized (Right-Hand Circular Polarization - RHCP) design to reduce Faraday loss. Our aim was to use fewer elements and achieve gain, so the antenna is constructed using 6x2 elements arranged in cross dipole and supported with a boom. We have achieved 10.67dBi at 146MHz and 9.28dBi at 437.5MHz.The process includes parameter optimization and fine-tuning of the Yagi-Uda array’s elements, such as the length and spacing of directors and reflectors, to achieve high gain and desirable radiation patterns. Furthermore, the optimization process considers the requirements for UHF and VHF frequency bands, ensuring broad frequency coverage for satellite reception. The results of this research are anticipated to significantly contribute to the advancement of satellite reception systems, enhancing their capabilities to reliably connect remote and underserved areas to the global communication network. Through innovative antenna design and simulation techniques, this study seeks to provide a foundation for the development of next-generation satellite communication infrastructure.

Keywords: Yagi-Uda antenna, RHCP, gain, UHF antenna, VHF antenna, CST, radiation pattern.

Procedia PDF Downloads 61

Authors: Efri Mardawati, Ronny Purwadi, Made Tri Ari Penia Kresnowati, Tjandra Setiadi

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EFB are mainly composed of cellulose (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). The palm oil empty fruit bunches (EFB) is the lignosellulosic waste from crude palm oil industries mainly compose of (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). Xylan, a polymer made of pentose sugar xylose and the most abundant component of hemicellulose in plant cell wall. Further xylose can be used as a raw material for production of a wide variety of chemicals such as xylitol, which is extensively used in food, pharmaceutical and thin coating applications. Currently, xylose is mostly produced from xylan via chemical hydrolysis processes. However, these processes are normally conducted at a high temperature and pressure, which is costly, and the required downstream processes are relatively complex. As an alternative method, enzymatic hydrolysis of xylan to xylose offers an environmentally friendly biotechnological process, which is performed at ambient temperature and pressure with high specificity and at low cost. This process is catalysed by xylanolytic enzymes that can be produced by some fungal species such as Aspergillus niger, Penicillium crysogenum, Tricoderma reseei, etc. Fungal that will be used to produce crude xylanase enzyme in this study is T. Viride ITB CC L.67. It is the purposes of this research to study the influence of pretreatment of EFB for the enzymatic hydrolysis process, optimation of temperature and pH of the hydrolysis process, the influence of substrate and enzyme concentration to the enzymatic hydrolysis process, the dynamics of hydrolysis process and followingly to study the kinetics of this process. Xylose as the product of enzymatic hydrolysis process analyzed by HPLC. The results show that the thermal pretreatment of EFB enhance the enzymatic hydrolysis process. The enzymatic hydrolysis can be well approached by the Michaelis Menten kinetic model, and kinetic parameters are obtained from experimental data.

Keywords: oil palm empty fruit bunches (EFB), xylose, enzymatic hydrolysis, kinetic modelling

Procedia PDF Downloads 389

Authors: Asavasereerat K., Teacharsripaitoon T., Tungyingyong P., Charupongrat S., Noppiboon S. Hochareon L., Kitsuban P.

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Third generation of vaccines is based on gene therapy where DNA is introduced into patients. The antigenic or therapeutic proteins encoded from transgenes DNA triggers an immune-response to counteract various diseases. Moreover, DNA vaccine offers the customization of its ability on protection and treatment with high stability. The production of DNA vaccines become of interest. According to USFDA guidance for industry, the recommended limits for impurities from host cell are lower than 1%, and the active conformation homogeneity supercoiled DNA, is more than 80%. Thus, the purification strategy using two-steps chromatography has been established and verified for its robustness. Herein, pVax1/lacZ, a pre-approved USFDA DNA vaccine backbone, was used and transformed into E. coli strain DH5α. Three purification process parameters including sample-loading flow rate, the salt concentration in washing and eluting buffer, were studied and the experiment was designed using response surface method with central composite face-centered (CCF) as a model. The designed range of selected parameters was 10% variation from the optimized set point as a safety factor. The purity in the percentage of supercoiled conformation obtained from each chromatography step, AIEX and HIC, were analyzed by HPLC. The response data were used to establish regression model and statistically analyzed followed by Monte Carlo simulation using SAS JMP. The results on the purity of the product obtained from AIEX and HIC are between 89.4 to 92.5% and 88.3 to 100.0%, respectively. Monte Carlo simulation showed that the pVAX1/lacZ purification process is robust with confidence intervals of 0.90 in range of 90.18-91.00% and 95.88-100.00%, for AIEX and HIC respectively.

Keywords: AIEX, DNA vaccine, HIC, puification, response surface method, robustness

Procedia PDF Downloads 206

Authors: Lingxiao Yang, Xin Wang, Bo Xu, Zhenqian Chen

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Due to its outstanding environmental performance, higher heating temperature and excellent low-temperature performance, transcritical carbon dioxide (CO₂) heat pumps are receiving more and more attention. However, improperly set operating parameters have a serious negative impact on the performance of the transcritical CO₂ heat pump due to the properties of CO₂. In this study, the heat transfer characteristics of the gas cooler are studied based on the modified “three-stage” gas cooler, then the effect of three operating parameters, compressor speed, gas cooler water-inlet flowrate and gas cooler water-inlet temperature, on the heating process of the system are investigated from the perspective of thermal quality and heat capacity. The results shows that: In the heat transfer process of gas cooler, the temperature distribution of CO₂ and water shows a typical “two region” and “three zone” pattern; The rise in the cooling pressure of CO₂ serves to increase the thermal quality on the CO₂ side of the gas cooler, which in turn improves the heating temperature of the system; Nevertheless, the elevated thermal quality on the CO₂ side can exacerbate the mismatch of heat capacity on both sides of the gas cooler, thereby adversely affecting the system coefficient of performance (COP); Furthermore, increasing compressor speed mitigates the mismatch in heat capacity caused by elevated thermal quality, which is exacerbated by decreasing gas cooler water-inlet flowrate and rising gas cooler water-inlet temperature; As a delegate, the varying compressor speed results in a 7.1°C increase in heating temperature within the experimental range, accompanied by a 10.01% decrease in COP and an 11.36% increase in heating capacity. This study can not only provide an important reference for the theoretical analysis and control strategy of the transcritical CO₂ heat pump, but also guide the related simulation and the design of the gas cooler. However, the range of experimental parameters in the current study is small and the conclusions drawn are not further analysed quantitatively. Therefore, expanding the range of parameters studied and proposing corresponding quantitative conclusions and indicators with universal applicability could greatly increase the practical applicability of this study. This is also the goal of our next research.

Keywords: transcritical CO₂ heat pump, gas cooler, heat capacity, thermal quality

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Authors: Bijit Kalita, R. Jayaganthan

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Additive manufacturing (AM) is a novel manufacturing method which provides more freedom in design, manufacturing near-net-shaped parts as per demand, lower cost of production, and expedition in delivery time to market. Among various metals, AM techniques, Laser Powder Bed Fusion (L-PBF) is the most prominent one that provides higher accuracy and powder proficiency in comparison to other methods. Particularly, 17-4 PH alloy is martensitic precipitation hardened (PH) stainless steel characterized by resistance to corrosion up to 300°C and tailorable strengthening by copper precipitates. Additively manufactured 17-4 PH stainless steel exhibited a dendritic/cellular solidification microstructure in the as-built condition. It is widely used as a structural material in marine environments, power plants, aerospace, and chemical industries. The excellent weldability of 17-4 PH stainless steel and its ability to be heat treated to improve mechanical properties make it a good material choice for L-PBF. In this study, the microstructures of martensitic stainless steels in the as-built state, as well as the effects of process parameters, building atmosphere, and heat treatments on the microstructures, are reviewed. Mechanical properties of fabricated parts are studied through micro-hardness and tensile tests. Tensile tests are carried out under different strain rates at room temperature. In addition, the effect of process parameters and heat treatment conditions on mechanical properties is critically reviewed. These studies revealed the performance of L-PBF fabricated 17–4 PH stainless-steel parts under cyclic loading, and the results indicated that fatigue properties were more sensitive to the defects generated by L-PBF (e.g., porosity, microcracks), leading to the low fracture strains and stresses under cyclic loading. Rapid melting, solidification, and re-melting of powders during the process and different combinations of processing parameters result in a complex thermal history and heterogeneous microstructure and are necessary to better control the microstructures and properties of L-PBF PH stainless steels through high-efficiency and low-cost heat treatments.

Keywords: 17–4 PH stainless steel, laser powder bed fusion, selective laser melting, microstructure, additive manufacturing

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Mohamed Noureldin, Jinkoo Kim

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The sensitivity of the seismic response parameters to the uncertain modeling variables of pile-founded fixed steel jacket platforms are investigated using tornado diagram, first-order second-moment, and static pushover analysis techniques. The effects of both aleatory and epistemic uncertainty on seismic response parameters have been investigated for an existing offshore platform. The sources of uncertainty considered in the present study are categorized into three different categories: the uncertainties associated with the soil-pile modeling parameters in clay soil, the platform jacket structure modeling parameters, and the uncertainties related to ground motion excitations. It has been found that the variability in parameters such as yield strength or pile bearing capacity has almost no effect on the seismic response parameters considered, whereas the global structural response is highly affected by the ground motion uncertainty. Also, some uncertainty in soil-pile property such as soil-pile friction capacity has a significant impact on the response parameters and should be carefully modeled. Based on the results, it is highlighted that which uncertain parameters should be considered carefully and which can be assumed with reasonable engineering judgment during the early structural design stage of fixed steel jacket platforms.

Keywords: fixed jacket offshore platform, pile-soil structure interaction, sensitivity analysis

Procedia PDF Downloads 375

Authors: Ajay Biswas, Swapan Bhaumik, Saurav Datta, Abhijit Bhowmik

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A series of experiments has been carried out to study the feasibility of submerged arc welding (SAW) on mild steel plate of designation IS 2062 grade B. Specimen temperature of which is reduced to zero degree Celsius whereas the ambient temperature is about 25-27 degree Celsius. To observe this, bead on plate submerged arc welding is formed on the specimen plate of heavy duty mild steel of designation IS 2062 grade B, fitted on the special fixture ensuring zero degree Celsius temperature to the specimen plate. Sixteen numbers of cold samples is welded by varying the most influencing parameters viz. voltage, wire feed rate, travel speed, and electrode stick-out at four different levels. Another sixteen numbers of specimens are at normal room temperature are welded by applying same combination of parameters. Those sixteen numbers of specimens are selected based on the design of experiment of Taguchi‘s L16 orthogonal array with the intension of reducing the number of experimental runs. Different attributes of bead geometry of the entire sample for both the situations are measured and compared. It is established that submerged arc welding is feasible at zero degree Celsius on mild steel plate of designation IS 2062 grade B and optimization of the process parameters can also be drawn as a clear response of parameters are obtained.

Keywords: submerged arc welding, zero degree celsius, Taguchi’s design of experiment, geometry of weldment

Procedia PDF Downloads 449

Authors: Ajay Biswas, Abhijit Bhowmik, Saurav Datta, Swapan Bhaumik

Abstract:

A series of experiments has been carried out to study the feasibility of submerged arc welding (SAW) on mild steel plate of designation IS 2062 grade B. Specimen temperature of which is reduced to zero degree Celsius whereas the ambient temperature is about 25-27 degree Celsius. To observe this, bead on plate submerged arc welding is formed on the specimen plate of heavy duty mild steel of designation IS 2062 grade B, fitted on the special fixture ensuring zero degree Celsius temperature to the specimen plate. Sixteen numbers of cold samples is welded by varying the most influencing parameters viz. Voltage, wire feed rate, travel speed and electrode stick-out at four different levels. Another sixteen numbers of specimens are at normal room temperature are welded by applying same combination of parameters. Those sixteen numbers of specimens are selected based on the design of experiment of Taguchi‘s L16 orthogonal array with the intension of reducing the number of experimental runs. Different attributes of bead geometry of the entire sample for both the situations are measured and compared. It is established that submerged arc welding is feasible at zero degree Celsius on mild steel plate of designation IS 2062 grade B and optimization of the process parameters can also be drawn as a clear response of parameters are obtained.

Keywords: geometry of weldment, submerged arc welding, Taguchi’s design of experiment, zero degree Celsius

Procedia PDF Downloads 433

Authors: M. G. Mostafa, Manjushree Chowdhury, Tapan Kumar Biswas, , Ananda Kumar Saha

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This study focused on effluents characterization and treatment process to reduce of toxicity from tannery effluents. Tanning industry is one of the oldest industries in the world. It is typically characterized as pollutants generated industries which produce wide varieties of high strength toxic chemicals. The study was conducted during the year 2008 to 2009 and the tannery effluents were collected three times in a year from the outlet of some selected leather industries located in Hagaribagh industrial zone Dhaka, Bangladesh. The analysis results of the raw effluents reveal that the effluents were yellowish-brown color, having basic pH, very high value of BOD5¬¬, COD, TDS, TSS, TS, and high concentrations of Cr, Na, SO42-, Cl- and other organic and inorganic constituents. The tannery effluents were treated with various doses of FeCl3 after settling and a subsequent filtration through sand-stone. The study observed that coagulant (FeCl3) 150 mg/L dose around neutral pH showed the best removal efficiency for major physico-chemical parameters. The analysis results of illustrate that the most of the physical and chemical parameters were found well below the prescribed permissible limits for effluent discharged. The study suggests that tannery effluents could be treated by a combined process consisting of settling, filtering and coagulating with FeCl3.

Keywords: characterization, effluent, tannery, treatment

Procedia PDF Downloads 450

Authors: Elitaria Bestri Agustina Siregar, Boni Fasius Siregar

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The paper concerned with the transitivity in the reading passage of English textbook for Senior High School. The six types of process were occurred in the passages with percentage as follows: Material Process is 166 (42%), Relational Process is 155 (39%), Mental Process is 39 (10%), Verbal Process is 21 (5%), Existential Process is 13 (3), and Behavioral Process is 5 (1%). The material processes were found to be the most frequently used process type in the samples in our corpus (41,60 %). This indicates that the twenty reading passages are centrally concerned with action and events. Related to developmental psychology theory, this book fits the needs of students of this age.

Keywords: transitivity, types of processes, reading passages, developmental psycholoy

Procedia PDF Downloads 414

Authors: Chi-Hao Yeh

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The aim of this paper is to show how to apply TRIZ to resolve conflicts in management area, which can be readily applied in new product development (NPD) process and Knowledge Management (KM) system in desinging and manfacturing stages. TRIZ has been well-known as a creative and innovative thinking theory in solving engineering and technology contradictions in the last two decades. However, few studies and practical usage were proposed in management area. Conflicts occurring including schedule, budget, and risk plannings at smart phone R&D process are discussed to demonstrate the ideas guided by 39 TRIZ management parameters, 40 TRIZ innovative principles, and contradiction matrix. The results show that TRIZ is able to provide direct, quick and effective alternatives to resolve the management conflicts. In this manner, huge effort and cost can be actually saved and practical experince can be stored in KM system. In this paper, an innovative 3C consuming product such as smart-phone is utilized as a case study to describe the proposed TRIZ-based conflicts-solving approaches in NPD process and Knowledge Management (KM) system.

Keywords: TRIZ, conflicts-solving in managment area, new product development (NPD), knowledge management (KM), smart-phone

Procedia PDF Downloads 519

Authors: T. Gomes, J. Manzi

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The inclusion of stirring systems in the calculation and optimization procedures has been undergone a significant lack of attention, what it can reflect in the results because such systems provide an additional energy to the process, besides promote a better distribution of mass and energy. This is meaningful for the reactive systems, particularly for the Continuous Stirred Tank Reactor (CSTR), for which the key variables and parameters, as well as the operating conditions of stirring systems, can play a pivotal role and it has been showed in the literature that neglect these factors can lead to sub-optimal results. It is also well known that the sole use of the First Law of Thermodynamics as an optimization tool cannot yield satisfactory results, since the joint use of the First and Second Laws condensed into a procedure so-called entropy generation minimization (EGM) has shown itself able to drive the system towards better results. Therefore, the main objective of this paper is to determine the effects of key parameters of the stirring system in the optimization procedures by means of EGM applied to the reactive systems. Such considerations have been possible by dimensional analysis according to Rayleigh and Buckingham's method, which takes into account the physical and geometric parameters and the variables of the reactive system. For the simulation purpose based on the production of propylene glycol, the results have shown a significant increase in the conversion rate from 36% (not-optimized system) to 95% (optimized system) with a consequent reduction of by-products. In addition, it has been possible to establish the influence of the work of the stirrer in the optimization procedure, in which can be described as a function of the fluid viscosity and consequently of the temperature. The conclusions to be drawn also indicate that the use of the entropic analysis as optimization tool has been proved to be simple, easy to apply and requiring low computational effort.

Keywords: stirring systems, entropy, reactive system, optimization

Procedia PDF Downloads 245

Authors: Bouafia-Chergui Souâd, Chabani Malika, Bensmaili Aicha

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Water treatment and especially, medicament pollutants are nowadays important problems. Degradation of oxytetracycline was carried out using combined process of low-frequency ultrasound (US), ultraviolet irradiation and a catalyst. The effectiveness of the coupled processes has been evaluated by studying the effects of various operating parameters including initial OTC concentration, solution pH and catalyst mass. For the photolysis process, the monochromatic ultraviolet light wavelength utilized was 365 nm. The sonolysis experiments were performed with ultrasound at a frequency of 40 kHz. The heterogeneous photocatalysis was studied in the presence of TiO2. The processes were employed individually, and simultaneously to examine the details of the processes and to investigate the contribution of each process. Low UV intensity (12W), low pH and high mass of TiO2 conditions enhanced the sono-photocatalytic degradation of OTC. The results showed that the individual contribution sonochemical and photochemical reactions are very low, however, their coupling increases the degradation rate of 8 times compared to photolysis and 2 times compared to sonolysis. There is a synergistic effect between the two modes of radiation, UV and U.S. leading to 82.04% degradation yield. An application of these combined processes on the treatment of a real pharmaceutical wastewater was examined.

Keywords: sonolysis, photocatalysis, combined process, antibiotic

Procedia PDF Downloads 286

Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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Rubber seed oil is an attractive alternative feedstock for biodiesel production because it is not related to food-chain plant. Rubber seed oil contains large amount of free fatty acids, which causes problem in biodiesel production. Free fatty acids can react with alkaline catalyst in biodiesel production. Acid esterification is used as pre-treatment to convert unwanted compound to desirable biodiesel. Phase separation of oil and methanol occurs at low ratio of methanol to oil and causes low reaction rate and conversion. Acid esterification requires large excess of methanol in order to increase the miscibility of methanol in oil and accordingly, it is a more expensive separation process. In this work, the kinetics of esterification of rubber seed oil with methanol is developed from available experimental results. Reactive distillation process was designed by using Aspen Plus program. The effects of operating parameters such as feed ratio, molar reflux ratio, feed temperature, and feed stage are investigated in order to find the optimum conditions. Results show that the reactive distillation process is proved to be better than conventional process. It consumes less feed methanol and less energy while yielding higher product purity than the conventional process. This work can be used as a guideline for further development to industrial scale of biodiesel production using reactive distillation.

Keywords: biodiesel, reactive distillation, rubber seed oil, transesterification

Procedia PDF Downloads 351

Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 297

Authors: Bharti Verma, Chandrajit Balomajumder

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Water pollution is escalated owing to industrialization and random ejection of one or more toxic heavy metal ions from the semiconductor industry, electroplating, metallurgical, mining, chemical manufacturing, tannery industries, etc., In semiconductor industry various kinds of chemicals in wafers preparation are used . Fluoride, toxic solvent, heavy metals, dyes and salts, suspended solids and chelating agents may be found in wastewater effluent of semiconductor manufacturing industry. Also in the chrome plating, in the electroplating industry, the effluent contains heavy amounts of Chromium. Since Cr(VI) is highly toxic, its exposure poses an acute risk of health. Also, its chronic exposure can even lead to mutagenesis and carcinogenesis. On the contrary, Cr (III) which is naturally occurring, is much less toxic than Cr(VI). Discharge limit of hexavalent chromium and trivalent chromium are 0.05 mg/L and 5 mg/L, respectively. There are numerous methods such as adsorption, chemical precipitation, membrane filtration, ion exchange, and electrochemical methods for the heavy metal removal. The present study focuses on the removal of Chromium ions by using flat sheet UF5kDa membrane. The Ultra filtration membrane process is operated above micro filtration membrane process. Thus separation achieved may be influenced due to the effect of Sieving and Donnan effect. Ultrafiltration is a promising method for the rejection of heavy metals like chromium, fluoride, cadmium, nickel, arsenic, etc. from effluent water. Benefits behind ultrafiltration process are that the operation is quite simple, the removal efficiency is high as compared to some other methods of removal and it is reliable. Polyamide membranes have been selected for the present study on rejection of Cr(VI) from feed solution. The objective of the current work is to examine the rejection of Cr(VI) from aqueous feed solutions by flat sheet UF5kDa membranes with different parameters such as pressure, feed concentration and pH of the feed. The experiments revealed that with increasing pressure, the removal efficiency of Cr(VI) is increased. Also, the effect of pH of feed solution, the initial dosage of chromium in the feed solution has been studied. The membrane has been characterized by FTIR, SEM and AFM before and after the run. The mass transfer coefficients have been estimated. Membrane transport parameters have been calculated and have been found to be in a good correlation with the applied model.

Keywords: heavy metal removal, membrane process, waste water treatment, ultrafiltration

Procedia PDF Downloads 139

Authors: Derradji Chebli, Abdallah Bouguettoucha, Abdelbaki Reffas Khalil Guediri, Abdeltif Amrane

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The removal of Methyl Green dye (MG) from aqueous solutions using modified P-brutia cones (PBH and PBN), has been investigated work. The physical parameters such as pH, temperature, initial MG concentration, ionic strength are examined in batch experiments on the sorption of the dye. Adsorption removal of MG was conducted at natural pH 4.5 because the dye is only stable in the range of pH 3.8 to 5. It was observed in experiments that the P-brutia cones treated with NaOH (PBN) exhibited high affinity and adsorption capacity compared to the MG P-brutia cones treated with HCl (PBH) and biosorption capacity of modified P-brutia cones (PBN and PBH) was enhanced by increasing the temperature. This is confirmed by the thermodynamic parameters (ΔG° and ΔH°) which show that the adsorption of MG was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase in the randomness for both adsorbent (PBN and PBH) during the adsorption process. The kinetic model pseudo-first order, pseudo-second order, and intraparticle diffusion coefficient were examined to analyze the sorption process; they showed that the pseudo-second-order model is the one that best describes the adsorption process (MG) on PBN and PBH with a correlation coefficient R²> 0.999. The ionic strength has shown that it has a negative impact on the adsorption of MG on two supports. A reduction of 68.5% of the adsorption capacity for a value Ce=30 mg/L was found for the PBH, while the PBN did not show a significant influence of the ionic strength on adsorption especially in the presence of NaCl. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P-brutia cones with a correlation factor R²>0.999. The capacity adsorption of P-brutia cones, was confirmed for the removal of a dye, MG, from aqueous solution. We note also that P-brutia cones is a material very available in the forest and low-cost biomaterial

Keywords: adsorption, p-brutia cones, forest wastes, dyes, isotherm

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Authors: Ramezani M., Neitzert T.

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This paper investigates mechanical properties and formability of the AZ61 magnesium alloy at high temperatures. Tensile tests were performed at elevated temperatures of up to 400ºC. The results showed that as temperature increases, yield strength and ultimate tensile strength decrease significantly, while the material experiences an increase in ductility (maximum elongation before break). A finite element model has been developed to further investigate the formability of the AZ61 alloy by deep drawing a square cup. Effects of different process parameters such as punch and die geometry, forming speed and temperature as well as blank-holder force on deep drawability of the AZ61 alloy were studied and optimum values for these parameters are achieved which can be used as a design guide for deep drawing of this alloy.

Keywords: AZ61, formability, magnesium, mechanical properties

Procedia PDF Downloads 579

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 75

Authors: Ravi Raj, Louis Chiu, Deepak Marla, Aijun Huang

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Hybridization of the directed laser deposition (DLD) process using an in-situ micro-roller to impart a vertical compressive load on the deposited bead at elevated temperatures can relieve tensile residual stresses incurred in the process. To investigate this stress relief mechanism and its relationship with the in-situ rolling parameters, a fully coupled dynamic thermo-mechanical model is presented in this study. A single bead deposition of Ti-6Al-4V alloy with an in-situ roller made of mild steel moving at a constant speed with a fixed nominal bead reduction is simulated using the explicit solver of the finite element software, Abaqus. The thermal model includes laser heating during the deposition process and the heat transfer between the roller and the deposited bead. The laser heating is modeled using a moving heat source with a Gaussian distribution, applied along the pre-formed bead’s surface using the VDFLUX Fortran subroutine. The bead’s cross-section is assumed to be semi-elliptical. The interfacial heat transfer between the roller and the bead is considered in the model. Besides, the roller is cooled internally using axial water flow, considered in the model using convective heat transfer. The mechanical model for the bead and substrate includes the effects of rolling along with the deposition process, and their elastoplastic material behavior is captured using the J2 plasticity theory. The model accounts for strain, strain rate, and temperature effects on the yield stress based on Johnson-Cook’s theory. Various aspects of this material behavior are captured in the FE software using the subroutines -VUMAT for elastoplastic behavior, VUHARD for yield stress, and VUEXPAN for thermal strain. The roller is assumed to be elastic and does not undergo any plastic deformation. Also, contact friction at the roller-bead interface is considered in the model. Based on the thermal results of the bead, the distance between the roller and the deposition nozzle (roller o set) can be determined to ensure rolling occurs around the beta-transus temperature for the Ti-6Al-4V alloy. It is identified that roller offset and the nominal bead height reduction are crucial parameters that influence the residual stresses in the hybrid process. The results obtained from a simulation at roller offset of 20 mm and nominal bead height reduction of 7% reveal that the tensile residual stresses decrease to about 52% due to in-situ rolling throughout the deposited bead. This model can be used to optimize the rolling parameters to minimize the residual stresses in the hybrid DLD process with in-situ micro-rolling.

Keywords: directed laser deposition, finite element analysis, hybrid in-situ rolling, thermo-mechanical model

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Authors: Reza Vakili

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The aim of this experiment was to optimize the effect of moisture, the production rate, grain particle size and steam conditioning temperature on pellet quality in broiler feed using Taguchi method and a 43 fractional factorial arrangement was conducted. Production rate, steam conditioning temperatures, particle sizes and moisture content were performed. During the production process, sampling was done, and then pellet durability index (PDI) and hardness evaluated in broiler feed grower and finisher. There was a significant effect of processing parameters on PDI and hardness. Based on the results of this experiment Taguchi method can be used to find the best combination of factors for optimal pellet quality.

Keywords: broiler, feed physical quality, hardness, processing parameters, PDI

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Authors: Mohannad Mayyas, Farshid Pahlevani, Veena Sahajwalla

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Automotive shredder residue (ASR) is an industrial waste, generated during the recycling process of End-of-life vehicles. The large increasing production volumes of ASR and its hazardous content have raised concerns worldwide, leading some countries to impose more restrictions on ASR waste disposal and encouraging researchers to find efficient solutions for ASR processing. Although a great deal of research work has been carried out, all proposed solutions, to our knowledge, remain commercially and technically unproven. While the volume of waste materials continues to increase, the production of materials from new sustainable sources has become of great importance. Advanced ceramic materials such as nitrides, carbides and borides are widely used in a variety of applications. Among these ceramics, a great deal of attention has been recently paid to Titanium nitride (TiN) owing to its unique characteristics. In our study, we propose a new sustainable approach for ASR management where TiN nanoparticles with ideal particle size ranging from 200 to 315 nm can be synthesized as a by-product. In this approach, TiN is thermally synthesized by nitriding pressed mixture of automotive shredder residue (ASR) incorporated with titanium oxide (TiO2). Results indicated that TiO2 influences and catalyses degradation reactions of ASR and helps to achieve fast and full decomposition. In addition, the process resulted in titanium nitride (TiN) ceramic with several unique structures (porous nanostructured, polycrystalline, micro-spherical and nano-sized structures) that were simply obtained by tuning the ratio of TiO2 to ASR, and a product with appreciable TiN content of around 85% was achieved after only one hour nitridation at 1550 °C.

Keywords: automotive shredder residue, nano-ceramics, waste treatment, titanium nitride, thermal conversion

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Authors: Mustafa Albayrak, Mete Onur Kaman, Ilyas Bozkurt

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In this study, the necessary material parameters were determined to be able to conduct progressive damage analysis of layered composites under low velocity impact by using the MAT162 material module in the LS-DYNA program. The material module MAT162 based on Hashin failure criterion requires 34 parameters in total. Some of these parameters were obtained directly as a result of dynamic and quasi-static mechanical tests, and the remaining part was calibrated and determined by comparing numerical and experimental results. Woven glass/epoxy was used as the composite material and it was produced by vacuum infusion method. In the numerical model, composites are modeled as three-dimensional and layered. As a result, the acquisition of MAT162 material module parameters, which will enable progressive damage analysis, is given in detail and step by step, and the selection methods of the parameters are explained. Numerical data consistent with the experimental results are given in graphics.

Keywords: Composite Impact, Finite Element Simulation, Progressive Damage Analyze, LS-DYNA, MAT162

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Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

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Samarium as a rare-earth element is playing a growing important role in high technology. Traditional methods for extraction of rare earth metals such as ion exchange and solvent extraction have disadvantages of high investment and high energy consumption. Emulsion liquid membrane (ELM) as an improved solvent extraction technique is an effective transport method for separation of various compounds from aqueous solutions. In this work, the extraction of samarium from aqueous solutions by ELM was investigated using response surface methodology (RSM). The organic membrane phase of the ELM was a nanofluid consisted of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as mobile carrier, and kerosene as base fluid. 1 M nitric acid solution was used as internal aqueous phase. The effects of the important process parameters on samarium extraction were investigated, and the values of these parameters were optimized using the Central Composition Design (CCD) of RSM. These parameters were the concentration of MWCNT in nanofluid, the carrier concentration, and the volume ratio of organic membrane phase to internal phase (Roi). The three-dimensional (3D) response surfaces of samarium extraction efficiency were obtained to visualize the individual and interactive effects of the process variables. A regression model for % extraction was developed, and its adequacy was evaluated. The result shows that % extraction improves by using MWCNT nanofluid in organic membrane phase and extraction efficiency of 98.92% can be achieved under the optimum conditions. In addition, demulsification was successfully performed and the recycled membrane phase was proved to be effective in the optimum condition.

Keywords: Cyanex 272, emulsion liquid membrane, MWCNT nanofluid, response surface methology, Samarium

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Authors: Sanjaykumar R. Patel, Parth R. Kayastha

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α-lactose monohydrate is widely used in the pharmaceutical industries as an inactive substance that acts as a vehicle or a medium for a drug or other active substance. It is a byproduct of dairy industries, and the recovery of lactose from whey not only boosts the improvement of the economics of whey utilization but also causes a reduction in pollution as lactose recovery can reduce the BOD of whey by more than 80%. In the present study, levels of process parameters were kept as initial lactose concentration (30-50% w/w), sonication amplitude (20-40%), sonication time (2-6 hours), and crystallization temperature (10-20 ^oC) for the recovery of lactose in ultrasound assisted cooling crystallization. In comparison with cooling crystallization, the use of ultrasound enhanced the lactose recovery by 39.17% (w/w). The parameters were optimized for the lactose recovery using Taguchi Method. The optimum conditions found were initial lactose concentration at level 3 (50% w/w), amplitude of sonication at level 2 (40%), the sonication time at level 3 (6 hours), and crystallization temperature at level 1 (10 °C). The maximum recovery was found to be 85.85% at the optimum conditions. Sonication time and the initial lactose concentration were found to be significant parameters for the lactose recovery.

Keywords: crystallization, lactose, Taguchi method, ultrasound

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Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

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This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

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Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system, thus, the proposed solution has been verified. The paper documents how it is possible to apply new discovery knowledge to be used in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: hierarchical process control, knowledge discovery from databases, neural network, process control

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: A. M. Khourshid, A. M. El-Kassas, I. Sabry

Abstract:

The objective of this work was to investigate the mechanical properties in order to demonstrate the feasibility of friction stir welding for joining Al 6061 aluminium alloys. Welding was performed on pipe with different thickness (2, 3 and 4 mm), five rotational speeds (485, 710, 910, 1120 and 1400 rpm) and a traverse speed of 4mm/min. This work focuses on two methods which are artificial neural networks using software and Response Surface Methodology (RSM) to predict the tensile strength, the percentage of elongation and hardness of friction stir welded 6061 aluminium alloy. An Artificial Neural Network (ANN) model was developed for the analysis of the friction stir welding parameters of 6061 pipe. Tensile strength, the percentage of elongation and hardness of weld joints were predicted by taking the parameters tool rotation speed, material thickness and axial force as a function. A comparison was made between measured and predicted data. Response Surface Methodology (RSM) was also developed and the values obtained for the response tensile strength, the percentage of elongation and hardness are compared with measured values. The effect of FSW process parameters on mechanical properties of 6061 aluminium alloy has been analysed in detail.

Keywords: friction stir welding, aluminium alloy, response surface methodology, artificial neural network

Procedia PDF Downloads 293