Search results for: optimization of steel

Authors: Karima Megdouli

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The ejector, a central element within the CO₂ transcritical ejection refrigeration system, holds significant importance in enhancing refrigeration capacity and minimizing compressor power usage. This study's objective is to introduce a technique for enhancing the effectiveness of the CO₂ transcritical two-phase ejector, utilizing Taguchi and ANOVA analysis. The investigation delves into the impact of geometric parameters, secondary flow temperature, and primary flow pressure on the efficiency of the ejector. Results indicate that employing a combination of Taguchi and ANOVA offers increased reliability and superior performance when optimizing the design of the CO₂ two-phase ejector.

Keywords: ejector, supersonic, Taguchi, ANOVA, optimization

Procedia PDF Downloads 88

Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

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The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: fatigue life, finite element analysis, tolerance analysis, optimization

Procedia PDF Downloads 157

Authors: Jun-Ho Chung, Sung-Hyun Yoo, In-Hwan Choi, Hyun-Kook Lee, Moon-Kyu Song, Choon-Ki Ahn

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The extended finite impulse response (EFIR) filter is addressed to optimize membership functions (MFs) of the fuzzy model that has strong nonlinearity. MFs are important parts of the fuzzy logic system (FLS) and, thus optimizing MFs of FLS is one of approaches to improve the performance of output. We employ the EFIR as an alternative optimization option to nonlinear fuzzy model. The performance of EFIR is demonstrated on a fuzzy cruise control via a numerical example.

Keywords: fuzzy logic system, optimization, membership function, extended FIR filter

Procedia PDF Downloads 723

Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

Procedia PDF Downloads 139

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

Procedia PDF Downloads 111

Authors: Alan Vaško, Juraj Belan, Lenka Hurtalová, Eva Tillová

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The aim of this study is to evaluate the influence of raw material composition on the microstructure, mechanical and fatigue properties and micromechanisms of failure of nodular cast iron. In order to evaluate the influence of charge composition, the structural analysis, mechanical and fatigue tests and micro fractographic analysis were carried out on specimens of ten melts with different charge compositions. The basic charge of individual melts was formed by a different ratio of pig iron and steel scrap and by different additive for regulation of chemical composition (silicon carbide or ferrosilicon). The results show differences in mechanical and fatigue properties, which are connected with the microstructure. SiC additive positively influences microstructure. Consequently, mechanical and fatigue properties of nodular cast iron are improved, especially in the melts with the higher ratio of steel scrap in the charge.

Keywords: nodular cast iron, silicon carbide, microstructure, mechanical properties

Procedia PDF Downloads 582

Authors: Kamal Upadhyay, Zhou Hua, Yu Rui

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This paper aims to improve the streamline linked with the flow field and cavitation on the valve sleeve. We observed that local pressure fluctuation produces a low-pressure zone, central to the formation of vapor volume fraction within the valve chamber led to air-bubbles (or cavities). Thus, it allows simultaneously to a severe negative impact on the inner surface and lifespan of the valve sleeves. Cavitation reduction is a vitally important issue to pressure control valves. The optimization of the flow field is proposed in this paper to reduce the cavitation of valve sleeves. In this method, the inner wall of the valve sleeve is changed from a cylindrical surface to the conical surface, leading to the decline of the fluid flow velocity and the rise of the outlet pressure. Besides, the streamline is distributed inside the sleeve uniformly. Thus, the bubble generation is lessened. The fluid models are built and analysis of flow field distribution, pressure, vapor volume and velocity was carried out using computational fluid dynamics (CFD) and numerical technique. The results indicate that this structure can suppress the cavitation of valve sleeves effectively.

Keywords: streamline, cavitation, optimization, computational fluid dynamics

Procedia PDF Downloads 145

Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

Procedia PDF Downloads 252

Authors: Sourabh R. Dinde, Rajshekar S. Talikoti

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According to the structural point of view Industrial Pallet rack structure can be considered typical steel framed structure. This work presents a general analysis of an industrial pallet rack structure, evaluating the influence of each of the components on the global stability. An analytical study for the sensitivity of pallet rack configuration in linear static equivalent lateral loads. The aim is to braced/unbraced frames were design and their analytical models are to be built in software. The finite element analysis is used to determine axial forces in beam and column, maximum storey displacement and buckling loads on braced/unbraced pallet rack structure. Bracing systems are mostly provided to enhance the stiffness factor of the structures with the seismic loads. Unbraced systems have mostly translational modes of failure and are very flexible due to excessive loads.

Keywords: buckling capacity, cold formed steel, finite element analysis, pallets Rrack, seismic design

Procedia PDF Downloads 326

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 291

Authors: Fares Senouci, Bachir Imine

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This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

Procedia PDF Downloads 252

Authors: Julien Monnier, Isabelle Mouton, Francois Buy, Adrien Michel, Sylvain Ringeval, Joel Malaplate, Caroline Toffolon, Bernard Marini, Audrey Lechartier

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Chosen to design and assemble massive components for nuclear industry, the 316 Nb austenitic stainless steel (also called 316 Nb) suits well this function thanks to its mechanical, heat and corrosion handling properties. However, these properties might change during steel’s life due to thermal ageing causing changes within its microstructure. Our main purpose is to determine if the 316 Nb will keep its mechanical properties after an exposition to industrial temperatures (around 300 °C) during a long period of time (< 10 years). The 316 Nb is composed by different phases, which are austenite as main phase, niobium-carbides, and ferrite remaining from the ferrite to austenite transformation during the process. Our purpose is to understand thermal ageing effects on the material microstructure and properties and to submit a model predicting the evolution of 316 Nb properties as a function of temperature and time. To do so, based on Fe-Cr and 316 Nb phase diagrams, we studied the thermal ageing of 316 Nb steel alloys (1%v of ferrite) and welds (10%v of ferrite) for various temperatures (350, 400, and 450 °C) and ageing time (from 1 to 10.000 hours). Higher temperatures have been chosen to reduce thermal treatment time by exploiting a kinetic effect of temperature on 316 Nb ageing without modifying reaction mechanisms. Our results from early times of ageing show no effect on steel’s global properties linked to austenite stability, but an increase of ferrite hardness during thermal ageing has been observed. It has been shown that austenite’s crystalline structure (cfc) grants it a thermal stability, however, ferrite crystalline structure (bcc) favours iron-chromium demixion and formation of iron-rich and chromium-rich phases within ferrite. Observations of thermal ageing effects on ferrite’s microstructure were necessary to understand the changes caused by the thermal treatment. Analyses have been performed by using different techniques like Atomic Probe Tomography (APT) and Differential Scanning Calorimetry (DSC). A demixion of alloy’s elements leading to formation of iron-rich (α phase, bcc structure), chromium-rich (α’ phase, bcc structure), and nickel-rich (fcc structure) phases within the ferrite have been observed and associated to the increase of ferrite’s hardness. APT results grant information about phases’ volume fraction and composition, allowing to associate hardness measurements to the volume fractions of the different phases and to set up a way to calculate α’ and nickel-rich particles’ growth rate depending on temperature. The same methodology has been applied to DSC results, which allowed us to measure the enthalpy of α’ phase dissolution between 500 and 600_°C. To resume, we started from mechanical and macroscopic measurements and explained the results through microstructural study. The data obtained has been match to CALPHAD models’ prediction and used to improve these calculations and employ them to predict 316 Nb properties’ change during the industrial process.

Keywords: stainless steel characterization, atom probe tomography APT, vickers hardness, differential scanning calorimetry DSC, thermal ageing

Procedia PDF Downloads 93

Authors: Agata Tomaszewska, Timothy Kamps, Stephan R. Turnock, Nicola Symonds

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Bob skeleton is a highly competitive sport in which an athlete reaches speeds up to 40 m/s sliding, head first, down an ice track. It is believed that the friction between the runners and ice significantly contributes to the amount of the total energy loss during a bob skeleton descent. There is only limited available experimental data regarding the friction of bob skeleton runners or indeed steel on the ice at high sliding speeds ( > 20 m/s). Testing methods used to investigate the friction of steel on ice in winter sports have been outlined, and their accuracy and repeatability discussed. A system thinking approach was used to investigate the runner-ice interaction during sliding and create concept designs of three ice tribometers. The operational envelope of the bob skeleton system has been defined through mathematical modelling. Designs of a drum, linear and inertia pin-on-disk tribometers were developed specifically for bob skeleton runner testing with the requirement of reaching up to 40 m/s speed and facilitate fresh ice sliding. The design constraints have been outline and the proposed solutions compared based on the ease of operation, accuracy and the development cost.

Keywords: bob skeleton, ice friction, high-speed tribometers, sliding friction

Procedia PDF Downloads 261

Authors: Behzad Mohammadzadeh, Huyk Chun Noh

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The plate is one of the popular structural elements used in a wide range of industries and structures. They may be subjected to blast loads during explosion events, missile attacks or aircraft attacks. This study is to investigate dynamic responses of the rectangular plate subjected to explosive loads. The effects of material properties and plate thickness on responses of the plate are to be investigated. The compressive pressure is applied to the surface of the plate. Different amounts of thickness in the range from 10mm to 30mm are considered for the plate to evaluate the changes in responses of the plate with respect to the plate thickness. Two different properties are considered for the steel. First, the analysis is performed by considering only the elastic-plastic properties for the steel plate. Later on damping is considered to investigate its effects on the responses of the plate. To do analysis, the numerical method using a finite element based package ABAQUS is applied. Finally, dynamic responses and graphs showing the relation between maximum displacement of the plate and aim parameters are provided.

Keywords: impulsive loaded plates, dynamic analysis, ABAQUS, material nonlinearity

Procedia PDF Downloads 523

Authors: Hadjadj Naima, K. Mahdi, D. Belhachat, F. S. Ait Chaouche, A. Ferradji

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The Nigella Sativa oil yield extracted by hydraulic pressing is influenced by the pressure temperature and size particles. The optimization of oil extraction is investigated. The rate of extraction of the whole seeds is very weak, a crushing of seeds is necessary to facilitate the extraction. This rate augments with the rise of the temperature and the pressure, and decrease of size particles. The best output (66%) is obtained for a granulometry lower than 1mm, a temperature of 50°C and a pressure of 120 bars.

Keywords: oil, Nigella sativa, extraction, optimization, temperature, pressure

Procedia PDF Downloads 480

Authors: J. Thiele

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Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

Procedia PDF Downloads 126

Authors: Mahdi Shokrollahi

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Over the past years, much research has been conducted on the vulnerability of structures to earthquakes, which only horizontal components of the earthquake were considered in their seismic analysis and vertical earthquake acceleration especially in near-fault area was less considered. The investigation of the mappings shows that vertical earthquake acceleration can be significantly closer to the maximum horizontal earthquake acceleration, and even exceeds it in some cases. This study has compared the behavior of different members of three steel moment frame with a buckling-restrained brace (BRB), one time only by considering the horizontal component and again by considering simultaneously the horizontal and vertical components under the three mappings of the near-fault area and the effect of vertical acceleration on structural responses is investigated. Finally, according to the results, the vertical component of the earthquake has a greater effect on the axial force of the columns and the vertical displacement of the middle of the beams of the different classes and less on the lateral displacement of the classes.

Keywords: vertical earthquake acceleration, near-fault area, steel frame, horizontal and vertical component of earthquake, buckling-restrained brace

Procedia PDF Downloads 179

Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

Procedia PDF Downloads 407

Authors: Mohamed Yousef, Magdy Samuel, Maha El-Meligy, Taher El-Bitar

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The present work is dealing with 2% Si-steel alloy. The alloy contains 0.05% C as well as 0.85% Al. The alloy under investigation would be used for electrical transformation purposes. A heating (expansion) - cooling (contraction) dilation investigation was executed to detect the a, a+g, and g transformation temperatures at the inflection points of the dilation curve. On heating, primary a  was detected at a temperature range between room temperature and 687 ^oC. The domain of a+g was detected in the range between 687 ^oC and 746 ^oC. g phase exists in the closed g region at the range between 746 ^oC and 1043 ^oC. The domain of a phase appears again at a temperature range between 1043 and 1105 ^oC, and followed by secondary a at temperature higher than 1105 ^oC. A physical simulation of thermo-mechanical processing on the as-cast alloy was carried out. The simulation process took into consideration the hot flat rolling pilot plant parameters. The process was executed on the thermo-mechanical simulator (Gleeble 3500). The process was designed to include seven consecutive passes. The 1^st pass represents the roughing stage, while the remaining six passes represent finish rolling stage. The whole process was executed at the temperature range from 1100 ^oC to 900 ^oC. The amount of strain starts with 23.5% at the roughing pass and decreases continuously to reach 7.5 % at the last finishing pass. The flow curve of the alloy can be abstracted from the stress-strain curves representing simulated passes. It shows alloy hardening from a pass to the other up to pass no. 6, as a result of decreasing the deformation temperature and increasing of cumulative strain. After pass no. 6, the deformation process enhances the dynamic recrystallization phenomena to appear, where the z-parameter would be high.

Keywords: si- steel, hot deformability, critical transformation temperature, physical simulation, thermo-mechanical processing, flow curve, dynamic softening.

Procedia PDF Downloads 245

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

Procedia PDF Downloads 449

Authors: Camilla G. Goncalves, Benedito Christ, Walter Miyakawa, Antonio J. Abdalla

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This work aims to investigate the properties and microstructure of diamond-like carbon film deposited by pulsed laser deposition by ablation of a graphite target in a vacuum chamber on a steel substrate. The equipment was mounted to provide one laser beam. The target of high purity graphite and the steel substrate were polished. The mechanical and tribological properties of the film were characterized using Raman spectroscopy, nanoindentation test, scratch test, roughness profile, tribometer, optical microscopy and SEM images. It was concluded that the pulsed laser deposition (PLD) technique associated with the low-pressure chamber and a graphite target provides a good fraction of sp3 bonding, that the process variable as surface polishing and laser parameter have great influence in tribological properties and in adherence tests performance. The optical microscopy images are efficient to identify the metallurgical bond.

Keywords: characterization, DLC, mechanical properties, pulsed laser deposition

Procedia PDF Downloads 153

Authors: Sohaibullah Zarghoon, Syed Yousaf, Cyril Belavy, Stanislav Duris, Samuel Emebu, Radek Matusu

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Induction heating is extensively employed in industrial furnaces due to its swift response and high energy efficiency. Designing and optimising these furnaces necessitates the use of computer-aided simulations. This study aims to develop an accurate temperature field model for a rectangular steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperature-dependent, and constant parameters of the steel billet. The resulting data-driven model was transformed into a state-space model using MATLAB's System Identification Toolbox for the purpose of designing a linear quadratic regulator (LQR). This controller was successfully implemented to regulate the core temperature of the billet from 1000°C to 1200°C, utilizing the distributed parameter system circuit.

Keywords: induction heating, LQR controller, skin depth, temperature field

Procedia PDF Downloads 42

Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

Procedia PDF Downloads 143

Authors: Olfat E. El-Azabawy, Enas M. Attia, Nadia Shawky, Amira M. Hypa

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In this work, an attempt is made to study the effects of orange peel extract (OPE) as an environment-friendly corrosion inhibitor for carbon steel (CS) within a formation water solution (FW). The study was performed in different concentrations (0.5-2.5% (v/v)) of peel extracts at ambient temperatures (25oC) and (2.5% (v/v)) at temperature range (25- 55 oC) by weight loss measurements, open circuit potential, potentiodynamic polarization and electrochemical impedance. The inhibition efficiency was calculated from all measurements and confirmed by energy-dispersive X-ray spectroscopy (EDS). Inhibition was found to increase with increasing inhibitors concentration and decrease with increasing temperature. It was seen that IE% is about 92.84% in the presence of 2.5% (v/v) of orange peel inhibitor by using weight loss method. The adsorption process was of physical type and obey Langmuir adsorption isotherm. Also, adsorption, as well as the inhibition process, followed first-order kinetics at all concentrations.

Keywords: eco-friendly corrosion inhibitor, OPE, oilfield water, electrochemical impedance

Procedia PDF Downloads 150

Authors: Siyang Wang, Yujin Hu, Xuelin Wang, Wenqian Zhang

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Austenitic stainless steels are widely used in nuclear industry to manufacture critical components owing to their excellent corrosion resistance at high temperatures. Almost all the components used in nuclear power plants are produced by surface finishing (surface cold work) such as milling, grinding and so on. The change of surface states induced by machining has great influence on the corrosion behavior. In the present study, long time oxidation behavior of machined 316 austenitic stainless steel exposed to simulated pressure water reactor environment was investigated considering different surface states. Four surface finishes were produced by electro-polishing (P), grinding (G), and two milling (M and M1) processes respectively. Before oxidation, the surface Vickers micro-hardness, surface roughness of each type of sample was measured. Corrosion behavior of four types of sample was studied by using oxidation weight gain method for six oxidation periods. The oxidation time of each period was 120h, 216h, 336h, 504h, 672h and 1344h, respectively. SEM was used to observe the surface morphology of oxide film in several period. The results showed that oxide film on austenitic stainless steel has a duplex-layer structure. The inner oxide film is continuous and compact, while the outer layer is composed of oxide particles. The oxide particle consisted of large particles (nearly micron size) and small particles (dozens of nanometers to a few hundred nanometers). The formation of oxide particle could be significantly affected by the machined surface states. The large particle on cold worked samples (grinding and milling) appeared earlier than electro-polished one, and the milled sample has the largest particle size followed by ground one and electro-polished one. For machined samples, the large particles were almost distributed along the direction of machining marks. Severe exfoliation was observed on one milled surface (M) which had the most heavily cold worked layer, while rare local exfoliation occurred on the ground sample (G) and the other milled sample (M1). The electro-polished sample (P) entirely did not exfoliate.

Keywords: austenitic stainless steel, oxidation, machining, SEM

Procedia PDF Downloads 287

Authors: C. D. Gomez-Esparza, Z. V. Hernandez-Castro, C. A. Rodriguez-Gonzalez, R. Martinez-Sanchez, A. Duarte-Moller

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Recently, the high entropy alloys (HEA) are the focus of attention in metallurgical and materials science due to their desirable and superior properties in comparison to conventional alloys. The HEA field has promoted the exploration of several compositions including the addition of non-metallic elements like carbon, which in traditional metallurgy is mainly used in the steel industry. The aim of this work was the synthesis of equiatomic FeCrNiMnTi high entropy alloys, with minor carbon content, by mechanical alloying and sintering. The effect of the addition of carbon nanotubes and graphite were evaluated by X-ray diffraction, scanning electron microscopy, and microhardness test. The structural and microstructural characteristics of the equiatomic alloys, as well as their hardness were compared with those of an austenitic AISI 321 stainless steel processed under the same conditions. The results showed that porosity in bulk samples decreases with carbon nanotubes addition, while the equiatomic composition favors the formation of titanium carbide and increased the AISI 321 hardness more than three times.

Keywords: carbon nanotubes, graphite, high entropy alloys, mechanical alloying

Procedia PDF Downloads 198

Authors: Yibin Qiu, Yubo Ouyang, Shihan Li, Guorui Zhang, Qi Li, Weirong Chen

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This paper aims at exploring the impacts of high dimensional dependencies of wind speed among wind farms on probabilistic optimal power flow. To obtain the reactive power optimization faster and more accurately, a mixture vine Copula structure model combining the K-means clustering, C vine copula and D vine copula is proposed in this paper, through which a more accurate correlation model can be obtained. Moreover, a Modified Backtracking Search Algorithm (MBSA), the three-point estimate method is applied to probabilistic optimal power flow. The validity of the mixture vine copula structure model and the MBSA are respectively tested in IEEE30 node system with measured data of 3 adjacent wind farms in a certain area, and the results indicate effectiveness of these methods.

Keywords: mixture vine copula structure model, three-point estimate method, the probability integral transform, modified backtracking search algorithm, reactive power optimization

Procedia PDF Downloads 248

Authors: Seyedamir Makinejadsanij

Abstract:

One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

Abstract:

Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Dimitrios J. Dimitriou

Abstract:

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: airport connectivity, inventory control, optimization, optimum allocation

Procedia PDF Downloads 334