Search results for: process parameters

Authors: Kalu Uka Orji, Nasiman Sapari, Khamaruzaman W. Yusof

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Exposure of galena (PbS), tealite (PbSnS2), and other associated minerals during mining activities release lead (Pb) and other heavy metals into the mining water through oxidation and dissolution. Heavy metal pollution has become an environmental challenge. Lead, for instance, can cause toxic effects to human health, including brain damage. Ex-mining pond water was reported to contain lead as high as 69.46 mg/L. Conventional treatment does not easily remove lead from water. A promising and emerging treatment technology for lead removal is the application of the electrocoagulation (EC) process. However, some of the problems associated with EC are systematic reactor design, selection of maximum EC operating parameters, scale-up, among others. This study investigated an EC process for the removal of lead from synthetic ex-mining pond water using a batch reactor and Fe electrodes. The effects of various operating parameters on lead removal efficiency were examined. The results obtained indicated that the maximum removal efficiency of 98.6% was achieved at an initial PH of 9, the current density of 15mA/cm2, electrode spacing of 0.3cm, treatment time of 60 minutes, Liquid Motion of Magnetic Stirring (LM-MS), and electrode arrangement = BP-S. The above experimental data were further modeled and optimized using a 2-Level 4-Factor Full Factorial design, a Response Surface Methodology (RSM). The four factors optimized were the current density, electrode spacing, electrode arrangements, and Liquid Motion Driving Mode (LM). Based on the regression model and the analysis of variance (ANOVA) at 0.01%, the results showed that an increase in current density and LM-MS increased the removal efficiency while the reverse was the case for electrode spacing. The model predicted the optimal lead removal efficiency of 99.962% with an electrode spacing of 0.38 cm alongside others. Applying the predicted parameters, the lead removal efficiency of 100% was actualized. The electrode and energy consumptions were 0.192kg/m3 and 2.56 kWh/m3 respectively. Meanwhile, the adsorption kinetic studies indicated that the overall lead adsorption system belongs to the pseudo-second-order kinetic model. The adsorption dynamics were also random, spontaneous, and endothermic. The higher temperature of the process enhances adsorption capacity. Furthermore, the adsorption isotherm fitted the Freundlish model more than the Langmuir model; describing the adsorption on a heterogeneous surface and showed good adsorption efficiency by the Fe electrodes. Adsorption of Pb2+ onto the Fe electrodes was a complex reaction, involving more than one mechanism. The overall results proved that EC is an efficient technique for lead removal from synthetic mining pond water. The findings of this study would have application in the scale-up of EC reactor and in the design of water treatment plants for feed-water sources that contain lead using the electrocoagulation method.

Keywords: ex-mining water, electrocoagulation, lead, adsorption kinetics

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Authors: S. J. Yune, K. H. Park

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The purpose of this study was to examine the validity of the research process for enhancing the humanities competence of the medical students. The research process was developed to be operated as a core subject course of 3 semesters. Among them, the research process for enhancing humanities capacity consisted of humanities and societies (6 teams) and education-psychology (2teams). The subjects of this study were 88-second grade students and 22 professors who participated in the research process. Among them, 13 professors participated in the study of humanities and 37 students. In the validity test, the professors were more likely to have more validity in the research process than the students in all areas of logic (p = .001), influence (p = .037), process (p = .001). The validity of the professor was higher than that of the students. The professors highly evaluated the students' learning outcomes and showed the most frequency to the prize group. As a result of analyzing the agreement between the students and the professors through the Kappa coefficient, the agreement degree of communication and cooperation competence was moderate to .430. Problem-solving ability was .340, which showed a fair degree of agreement. However, other factors showed only a slight degree of agreement of less than .20.

Keywords: research process, medical school, humanities competence, validity verification

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Authors: Surendra Choudhary, Sapan Tiwari

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The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Jixiang Zhang, Yanhua Wang

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A dynamic of Bertrand duopoly game is analyzed, where players use different production methods and choose their prices with bounded rationality. The equilibriums of the corresponding discrete dynamical systems are investigated. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability of Nash equilibrium, as some parameters of the model are varied, gives rise to complex dynamics such as cycles of higher order and chaos. On this basis, we discover that an increase of adjustment speed of bounded rational player can make Bertrand market sink into the chaotic state. Finally, the complex dynamics, bifurcations and chaos are displayed by numerical simulation.

Keywords: Bertrand duopoly model, discrete dynamical system, heterogeneous expectations, nash equilibrium

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Authors: Paramjit Kaur, Harish Kundra

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In the recent years, swarm intelligence based firefly algorithm has become a great focus for the researchers to solve the real time optimization problems. Here, firefly algorithm is used for the application of satellite image classification. For experimentation, Alwar area is considered to multiple land features like vegetation, barren, hilly, residential and water surface. Alwar dataset is considered with seven band satellite images. Firefly Algorithm is based on the attraction of less bright fireflies towards more brightener one. For the evaluation of proposed concept accuracy assessment parameters are calculated using error matrix. With the help of Error matrix, parameters of Kappa Coefficient, Overall Accuracy and feature wise accuracy parameters of user’s accuracy & producer’s accuracy can be calculated. Overall results are compared with BBO, PSO, Hybrid FPAB/BBO, Hybrid ACO/SOFM and Hybrid ACO/BBO based on the kappa coefficient and overall accuracy parameters.

Keywords: image classification, firefly algorithm, satellite image classification, terrain classification

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

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Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

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Authors: P. Sawitri, S. Cdr. Sittha, T. Kritsana

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Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.

Keywords: flow forming, pressure vessel, four rollers, feed rate, spindle speed, cold work

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Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: S. Sulaiman, M. A. Razak, M. R. Ibrahim, A. A. Khan

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An experimental work on the effect of different current and pulse duration on performance of EDM process of Allegheny Ludlum D2 Tool Steel (UNS T30402). The effect of varying the machining parameters on the machining responses such as material removal rate (MRR), electrode wear rate (EWR), and surface roughness (Ra) have been investigated. In this study, triangular shape and circular shape of copper was used as an electrode with surface area of 100 mm². The experiments were repeated for three different values of pulse duration (100 µs, 200 µs and 400 µs) with combination of three different values of discharge current (12 A, 16 A and 24 A). It was found that the pulse duration and current have significant effect on MRR, EWR and Ra. An increase in the pulse durations causes an increase in the MRR and Ra, but a decrease in the EWR. Meanwhile, the effect of currents on EDM performance shows that the increasing currents lead to an increase in the MRR, EWR and Ra.

Keywords: allegheny ludlum D2 tool steel, current, EDM, surface roughness, pulse duration

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Authors: Ahmed A. Khamis, Sherif A. Ibrahim, Mahmoud El Khatieb, Mohamed A. Barakat

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Parametric design is an icon of the modern architectural that facilitate taking complex design decisions counting on altering various design parameters. Double skin facades are one of the parametric applications for using parametric designs. This paper opts to enhance different daylight parameters of a selected case study office building in Cairo using parametric double skin facade. First, the design and optimization process executed utilizing Grasshopper parametric design software which is a plugin in rhino. The daylighting performance of the base case building model was compared with the one used the double façade showing an enhancement in daylighting performance indicators like glare and task illuminance in the modified model, execution drawings are made for the optimized design to be executed through Revit, followed by computerized digital fabrication stages of the designed model with various scales to reach the final design decisions using Simplify 3D for mock-up digital fabrication

Keywords: parametric design, double skin facades, digital fabrication, grasshopper, simplify 3D

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Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

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Authors: J. Martin, A. Nominé, T. Czerwiec, G. Henrion, T. Belmonte

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The plasma electrolytic oxidation (PEO) is a particular electrochemical process to produce protective oxide ceramic coatings on light-weight metals (Al, Mg, Ti). When applied to aluminum alloys, the resulting PEO coating exhibit improved wear and corrosion resistance because thick, hard, compact and adherent crystalline alumina layers can be achieved. Several investigations have been carried out to improve the efficiency of the PEO process and one particular way consists in tuning the suitable electrical regime. Despite the considerable interest in this process, there is still no clear understanding of the underlying discharge mechanisms that make possible metal oxidation up to hundreds of µm through the ceramic layer. A key parameter that governs the PEO process is the numerous short-lived micro-discharges (micro-plasma in liquid) that occur continuously over the processed surface when the high applied voltage exceeds the critical dielectric breakdown value of the growing ceramic layer. By using a bipolar pulsed current to supply the electrodes, we previously observed that micro-discharges are delayed with respect to the rising edge of the anodic current. Nevertheless, explanation of the origin of such phenomena is still not clear and needs more systematic investigations. The aim of the present communication is to identify the relationship that exists between this delay and the mechanisms responsible of the oxide growth. For this purpose, the delay of micro-discharges ignition is investigated as the function of various electrical parameters such as the current density (J), the current pulse frequency (F) and the anodic to cathodic charge quantity ratio (R = Qp/Qn) delivered to the electrodes. The PEO process was conducted on Al2214 aluminum alloy substrates in a solution containing potassium hydroxide [KOH] and sodium silicate diluted in deionized water. The light emitted from micro-discharges was detected by a photomultiplier and the micro-discharge parameters (number, size, life-time) were measured during the process by means of ultra-fast video imaging (125 kfr./s). SEM observations and roughness measurements were performed to characterize the morphology of the elaborated oxide coatings while XRD was carried out to evaluate the amount of corundum -Al203 phase. Results show that whatever the applied current waveform, the delay of micro-discharge appearance increases as the process goes on. Moreover, the delay is shorter when the current density J (A/dm2), the current pulse frequency F (Hz) and the ratio of charge quantity R are high. It also appears that shorter delays are associated to stronger micro-discharges (localized, long and large micro-discharges) which have a detrimental effect on the elaborated oxide layers (thin and porous). On the basis of the results, a model for the growth of the PEO oxide layers will be presented and discussed. Experimental results support that a mechanism of electrical charge accumulation at the oxide surface / electrolyte interface takes place until the dielectric breakdown occurs and thus until micro-discharges appear.

Keywords: aluminium, micro-discharges, oxidation mechanisms, plasma electrolytic oxidation

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Authors: Imam Asrowardi, Septafiansyah Dwi Putra, Eko Subyantoro

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Process assessments can improve IT service management system (IT SMS) processes but the assessment method is not always transparent. This paper outlines a project to develop a solution- mediated process assessment tool to enable transparent and objective SMS process assessment. Using the international standards for SMS and process assessment, the tool is being developed following the International standard approach in collaboration and evaluate by expert judgment from committee members and ITSM practitioners.

Keywords: SMS, tools evaluation, ITIL, ISO service

Procedia PDF Downloads 460

Authors: C. Venkataraman B. E., J. Nagarajan B. E., V. Srinivasan M. Tech

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For a better understanding on sulfide stress corrosion cracking, a theoretical approach based on crystal structure, molecule behavior, flow of electrons and electrochemical reaction is developed. Its impact on different materials such as carbon steel, low alloy, alloy for sour (H2S) environments is studied. This paper describes the theories on various disaster and failures occurred in the industry by Stress Corrosion Cracking (SCC). Parameters such as pH of process fluid, partial pressure of CO2, O2, Chlorine, effect of internal pressure (crystal structure deformation by stress), and external environment condition are considered. An analytical line graph is then created for process fluid parameter verses time, temperature, induced/residual stress due to local pressure build-up. By comparison with the load test result of NACE and ASTM, it is possible to predict and simplify the control of SCC by use of materials like ferritic, Austenitic material in the oil and gas & petroleum industries.

Keywords: crystal structure deformation, failure assessment, alloy-environment combination, H2S

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Authors: Jenq-Shyong Chen, Ben-Fong Yu

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CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

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Authors: Daniel Nelson, Valeria La Saponara

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Material extrusion is an additive manufacturing modality that continues to show great promise in the ability to create low-cost, highly intricate, and exceedingly useful structural elements. As more capable and versatile filament materials are devised, and the resolution of manufacturing systems continues to increase, the need to understand and predict manufacturing-induced warping will gain ever greater importance. The following study presents an in situ remote sensing and data analysis construct that allows for the in situ mapping and quantification of surface displacements induced by residual stresses on a specified test structure. This proof-of-concept experimental process shows that it is possible to provide designers and manufacturers with insight into the manufacturing parameters that lead to the manifestation of these deformations and a greater understanding of the behavior of these warping events over the course of the manufacturing process.

Keywords: additive manufacturing, deformation, digital image correlation, fused filament fabrication, residual stress, warping

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Authors: Ahmed H. Elkholy

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The concept of applying a prescribed oscillation to viscous fluids to aid or increase flow is used to produce a maintenance free pump. Application of this technique to fluids presents unique problems such as physical separation; control of heat and mass transfer in certain industrial applications; and improvement of some fluid process methods. The problem as stated is to obtain the velocity distribution, wall shear stress and energy expended when a pipe containing a stagnant viscous fluid is externally excited by a sinusoidal pulse, one end of the pipe being pinned. On the other hand, the effect of different parameters on the results are presented. Such parameters include fluid viscosity, frequency of oscillations and pipe geometry. It was found that the flow velocity through the pump is maximum at the pipe wall, and it decreases rapidly towards the pipe centerline. The frequency of oscillation should be above a certain value in order to obtain meaningful flow velocity. The amount of energy absorbed in the system is mainly due to pipe wall strain energy, while the fluid pressure and kinetic energies are comparatively small.

Keywords: sinusoidal excitation, pump, shear stress, flow

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Authors: Wahyu Eko Diyanto, Amalia Dyah Arumsari, Ulfatu Layinatinnahdiyah Arrosyadi

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Tofu industry is one of the local food industry which is can being competitive industry in the ASEAN Economic Community (AEC). However, a lot of tofu entrepreneurs just thinking how to produce good quality product without considering the impact of environmental conditions from the production process. Production of tofu per day requires a number of 15 kg with liquid waste generated is 652.5 liters. That liquid waste is discharged directly into waterways, whereas tofu liquid waste contains organic compounds that quickly unraveled, so it can pollute waterways. In addition, tofu liquid waste is high in Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solid (TSS), nitrogen and phosphorus. This research is aim to create a method of handling liquid waste effectively and efficiently by using water lettuce. The method is done by observation and experiment by using phytoremediation method in the tofu liquid waste using water lettuce and adding aeration to reduce the concentration of contaminants. The results of the research analyzed the waste quality standard parameters based on SNI (National Standardization Agency of Indonesia). The efficiency concentration and parameters average of tofu liquid waste are obtained pH 3,42% (from 4,0 to be 3,3), COD 76,13% (from 3579 ppm to be 854 ppm), BOD 55 % (from 11600 ppm to be 5242 ppm), TSS 93,6% (from 3174 ppm to be 203 ppm), turbidity is 64,8% (from 977 NTU to be 1013 NTU), and temperature 36oC (from 45oC to be 40oC). The efficiency of these parameters indicates a safe value for the effluent to be channeled in waterways. Water lettuce and tofu liquid waste phytoremediation result will be used as biogas as renewable energy.

Keywords: aeration, phytoremediation, water letuce, tofu liquid waste

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Authors: Wilhelm Hoeflinger, Thomas Laminger, Johannes Wolfslehner

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For vacuum cleaned dust filters, used e. g. in textile industry, there exist no calculation methods to determine design parameters (e. g. traverse speed of the nozzle, filter area...). In this work a method to calculate the optimum traverse speed of the nozzle of an industrial-size flat dust filter at a given mean pressure drop and filter face velocity was elaborated. Well-known equations for the design of a cleanable multi-chamber bag-house-filter were modified in order to take into account a continuously regeneration of a dust filter by a nozzle. Thereby, the specific filter medium resistance and the specific cake resistance values are needed which can be derived from filter tests under constant operation conditions. A lab-scale filter test rig was used to derive the specific filter media resistance value and the specific cake resistance value for vacuum cleaned filter operation. Three different filter media were tested and the determined parameters were compared to each other.

Keywords: design of dust filter, dust removing, filter regeneration, operation parameters

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Authors: Theena Thayalan, K. N. Ramesh Babu

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Machining induced residual stress (RS) is one of the most important surface integrity parameters that characterize the near surface layer of a mechanical component, which plays a crucial role in controlling the performance, especially its fatigue life. Since experimental determination of RS is expensive and time consuming, it would be of great benefit if they could be predicted. In such case, it would be possible to select the cutting parameters required to produce a favorable RS profile. In the present study, an effort has been made to develop a 'two dimensional finite element model (FEM)' to simulate orthogonal cutting process and to predict surface and sub-surface RS using the commercial FEA software DEFORM-2D. The developed finite element model has been validated through experimental investigation of RS. In the experimentation, the orthogonal cutting tests were carried out on AISI 4340 by varying the cutting speed (VC) and uncut chip thickness (f) at three levels and the surface & sub-surface RS has been measured using XRD and Electro polishing techniques. The comparison showed that the RS obtained using developed numerical model is in reasonable agreement with that of experimental data.

Keywords: FEM, machining, residual stress, XRF

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Authors: Javeed Akhtar, R. K. Pandey, Z. R. Azaz Ahmad Azad

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For the purpose of making different uses of food material for the development of extruded foods are produced using single and twin extruders. Extrusion cooking is a useful and economical tool for processing of novel food. This high temperature, short time processing technology causes chemical and physical changes that alter the nutritional and physical quality of the product. Extrusion processing of food ingredients characteristically depends on associating process conditions that influence the product qualities. The process parameters are optimized for extrusion of food material in order to obtain the maximum nutritive value by inactivating the anti-nutritional factors. The processing conditions such as moisture content, temperature and time are controlled to avoid over heating or under heating which otherwise would result in a product of lower nutritional quality.

Keywords: extrusion processing, single and twin extruder, operating condition of extruders and extruded novel foods, food and agricultural engineering

Procedia PDF Downloads 366

Authors: V. J. Pillewan, D. N. Raut, K. N. Patil, D. K. Shinde

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Forging, milling, turning, grinding and shaping etc. are the various industrial manufacturing processes which generate the metal waste. Grinding is extensively used in the finishing operation. The waste generated contains significant impurities apart from the metal particles. Due to these significant impurities, it becomes difficult to process and gets usually dumped in the landfills which create environmental problems. Therefore, it becomes essential to reuse metal waste to create value added products. Powder injection molding process is used for producing the porous metal matrix framework. This paper discusses the presented design of the porous framework to be used for the liquid filter application. Different parameters are optimized to obtain the better strength framework with variable porosity. Carbon nanotubes are used as reinforcing materials to enhance the strength of the metal matrix framework.

Keywords: grinding waste, powder injection molding (PIM), carbon nanotubes (CNTs), matrix composites (MMCs)

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Authors: Shreedevi Moharana, Subashisa Dutta

Abstract:

The present study focuses on the estimation of crop biophysical parameters like crop chlorophyll, nitrogen and water stress at plot scale in the crop fields. To achieve these, we have used high-resolution satellite LISS IV imagery. A new methodology has proposed in this research work, the spectral shape function of paddy crop is employed to get the significant wavelengths sensitive to paddy crop parameters. From the shape functions, regression index models were established for the critical wavelength with minimum and maximum wavelengths of multi-spectrum high-resolution LISS IV data. Moreover, the functional relationships were utilized to develop the index models. From these index models crop, biophysical parameters were estimated and mapped from LISS IV imagery at plot scale in crop field level. The result showed that the nitrogen content of the paddy crop varied from 2-8%, chlorophyll from 1.5-9% and water content variation observed from 40-90% respectively. It was observed that the variability in rice agriculture system in India was purely a function of field topography.

Keywords: crop parameters, index model, LISS IV imagery, plot scale, shape function

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Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

Abstract:

Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

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Authors: Abbas Al-Refaie

Abstract:

This paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L₉ array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for a tablet’s averages of weight, hardness, and thickness were improved to 1.03, 4.42, and 1.42, respectively. Such improvements resulted in significant savings in quality and production costs.

Keywords: fuzzy goal programming, control charts, process capability, tablet optimization

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Authors: Xiaoqin Wang, Li Yin

Abstract:

Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Dan Zhao, Y. W. Sheng

Abstract:

The present work considers a convection-driven T-shaped pulse combustion system. Both experimental and numerical investigations are conducted to study the mechanism of pulse combustion and its potential application in fabric drying. To gain insight on flame-acoustic dynamic interaction and pulsating flow characteristics, 3D numerical simulation of the pulse combustion process of a premixed turbulent flame in a Rijke-type combustor is performed. Two parameters are examined: (1) fuel-air ratio, (2) inlet flow velocity. Their effects on triggering pulsating flow and Nusselt number are studied. As each of the parameters is varied, Nusselt number characterizing the heat transfer rate and the heat-driven pulsating flow signature is found to change. The main nonlinearity is identified in the heat fluxes. To validate our numerical findings, a cylindrical T-shaped Rijke-type combustor made of quartz-glass with a Bunsen burner is designed and tested.

Keywords: pulse combustion, fabric drying, heat transfer, combustion oscillations, pressure oscillations

Procedia PDF Downloads 231