Search results for: industrial machine

Authors: S. Baghdar Hosseini, K. Bashirnezhad, A. R. Moghiman, Y. Khazraii, N. Nikoofal

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The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. Biodiesel is a renewable, domestically produced fuel that has been shown to reduce particulate, hydrocarbon, and carbon monoxide emissions from combustion. In the present study an experimental investigation on emission characteristic of a liquid burner system operating on several percentage of biodiesel and gas oil is carried out. Samples of exhaust gas are analysed with Testo 350 Xl. The results show that biodiesel can lower some pollutant such as CO, CO2 and particulate matter emissions while NOx emission would increase in comparison with gas oil. The results indicate there may be benefits to using biodiesel in industrial processes.

Keywords: Biodiesel, combustion, gas oil, pollutant.

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Authors: H. Rafiei, M. Rabbani

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This paper proposes a new decision making structure to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder, and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company. The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.

Keywords: Hybrid make-to-stock/make-to-order, Multi-attribute decision making, Order partitioning, Order penetration point.

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Hugo Sampaio Libero, Max de Castro Magalhaes

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The perception of sound radiated from a building floor is greatly influenced by the rooms in which it is immersed and by the position of both listener and source. The main question that remains unanswered is related to the influence of the source position on the sound power radiated by a complex wall-floor system in buildings. This research is concerned with the investigation of vibration transmission across walls and floors in buildings. It is primarily based on the determination of vibration reduction index via experimental tests. Knowledge of this parameter may help in predicting noise and vibration propagation in building components. First, the physical mechanisms involving vibration transmission across structural junctions is described. An experimental set-up is performed to aid this investigation. The experimental tests have showed that the vibration generation in the walls and floors are directed related to their size and boundary conditions. It is also shown that the vibration source position can affect the overall vibration spectrum significantly. Second, the characteristics of the noise spectra inside the rooms due to an impact source (tapping machine) are also presented. Conclusions are drawn for the general trend of vibration and noise spectrum of the structural components and rooms respectively. In summary, the aim of this paper is to investigate the vibro-acoustical behavior of building floors and walls under floor impact excitation. The impact excitation was at distinct positions on the slab. The analysis has highlighted the main physical characteristics of the vibration transmission mechanism.

Keywords: Vibration transmission, Vibration Reduction Index, Impact excitation, building acoustics.

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Authors: Zefry Darmawan, Shigeyuki Haruyama, Ken Kaminishi

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Product development is a big issue in the industrial competition and takes a serious part in development of technology. Product development process could adapt high changes of market needs and transform into engineering concept in order to produce high-quality product. One of the latest methods in product development is Analysis-Led-Design (ALD). It utilizes digital engineering design tools with finite analysis to perform product robust analysis and valuable for product reliability assurance. Heavy machinery which operates under severe condition should maintain safety to the customer when faced with potential hazard. Cab frame should able to absorb the energy while collision. Through ALD, a series of improvement of cab frame to increase energy absorption was made and analyzed. Improvement was made by modifying shapes of frame and-or install absorption device in certain areas. Simulation result showed that install absorption device could increase absorption energy than modifying shape.

Keywords: ALD, ROPS, energy absorption, cab frame.

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Authors: J. Chelladurai, G. Saravana Ilango, C. Nagamani, S. Senthil Kumar

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Pulse width modulation (PWM) techniques have been the subject of intensive research for different industrial and power sector applications. A large variety of methods, different in concept and performance, have been newly developed and described. This paper analyzes the comparative merits of Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques and the suitability of these techniques in a Shunt Active Filter (SAF). The objective is to select the scheme that offers effective utilization of DC bus voltage and also harmonic reduction at the input side. The effectiveness of the PWM techniques is tested in the SAF configuration with a non linear load. The performance of the SAF with the SPWM and (SVPWM) techniques are compared with respect to the THD in source current. The study reveals that in the context of closed loop SAF control with the SVPWM technique there is only a minor improvement in THD. The utilization of the DC bus with SVPWM is also not significant compared to that with SPWM because of the non sinusoidal modulating signal from the controller in SAF configuration.

Keywords: Voltage source inverter, Shunt active filter, SPWM, SVPWM, Matlab/SIMULINK.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Perminderjit Singh, Sukhvir Singh

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Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes. 

Keywords: Total quality management, critical success factor, employee satisfaction.

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Authors: Noboru Wakamoto, Kiyotaka Obunai, Kazuya Okubo, Toru Fujii

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The aim of this study is to moderate the dependence of counter frictional coefficient on temperature between counter surfaces and to reduce the wear of C/C composites at low temperature. To modify the C/C composites, Silica (SiO₂) powders were added into phenolic resin for carbon precursor. The preform plate of the precursor of C/C composites was prepared by conventional filament winding method. The C/C composites plates were obtained by carbonizing preform plate at 2200 °C under an argon atmosphere. At that time, the silicon carbides (SiC) were synthesized around the surfaces and the internal vacancies of the C/C composites. The frictional coefficient on the counter surfaces and specific wear volumes of the C/C composites were measured by our developed frictional test machine like pin-on disk type. The XRD indicated that SiC was synthesized in the body of C/C composite fabricated by current method. The results of friction test showed that coefficient of friction of unmodified C/C composites have temperature dependence when the test condition was changed. In contrast, frictional coefficient of the C/C composite modified with SiO₂ powders was almost constant at about 0.27 when the temperature condition was changed from Room Temperature (RT) to 300 °C. The specific wear rate decreased from 25×10^-6 mm²/N to 0.1×10^-6 mm²/N. The observations of the surfaces after friction tests showed that the frictional surface of the modified C/C composites was covered with a film produced by the friction. This study found that synthesizing SiC around surface and internal vacancies of C/C composites was effective to moderate the dependence on the frictional coefficient and reduce to the abrasion of C/C composites.

Keywords: C/C composites, frictional coefficient, SiC, wear.

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Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

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The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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Authors: Makoto Sakamoto, Yasuo Uchida, Makoto Nagatomo, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

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In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.

Keywords: computational complexity, cooperating system, finite automaton, four-dimension, hierarchy, multihead.

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Authors: Elangeshwaran Pathmanathan, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam

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This paper aims to develop a NOx emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). Malaysia DOE is actively imposing the Clean Air Regulation to mandate the installation of analytical instrumentation known as Continuous Emission Monitoring System (CEMS) to report emission level online to DOE . As a hardware based analyzer, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive technique is often preferred and considered as a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a LNG Complex. Simulated Annealing (SA) is first used to determine the initial hyperparameters which are then further optimized based on the performance of the model using Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on backpropagation neural networks (BPNN) in both training and testing data.

Keywords: artificial neural networks, industrial pollution, predictive algorithms, support vector machines

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Authors: R. Ibrahim, M. Azmirruddin, M. Jabir, N. Johari, M. Muhamad, A. R. A. Talib

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Inconel718 has been widely used as a super alloy in aerospace application due to the high strength at elevated temperatures, satisfactory oxidation resistance and heat corrosion resistance. In this study, the Inconel718 has been fabricated using high technology of Metal Injection Molding (MIM) process due to the cost effective technique for producing small, complex and precision parts in high volume compared with conventional method through machining. Through MIM, the binder system is one of the most important criteria in order to successfully fabricate the Inconel718. Even though, the binder system is a temporary, but failure in the selection and removal of the binder system will affect on the final properties of the sintered parts. Therefore, the binder system based on palm oil derivative which is palm stearin has been formulated and developed to replace the conventional binder system. The rheological studies of the mixture between the powder and binders system have been determined properly in order to be successful during injection into injection molding machine. After molding, the binder holds the particles in place. The binder system has to be removed completely through debinding step. During debinding step, solvent debinding and thermal pyrolysis has been used to remove completely of the binder system. The debound part is then sintered to give the required physical and mechanical properties. The results show that the properties of the final sintered parts fulfill the Standard Metal Powder Industries Federation (MPIF) 35 for MIM parts.

Keywords: Binder system, rheological study, metal injection molding, debinding and sintered parts.

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Authors: Lucie Novakova, Petr Homola, Vaclav Kafka

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Asymmetric incremental sheet forming (AISF) could significantly reduce costs incurred by the fabrication of complex industrial components with a minimal environmental impact. The AISF experiments were carried out on commercially pure titanium (Ti-Gr2), Timetal (15-3-3-3) alloy, and Ti-6Al-4V (Ti-Gr5) alloy. A special testing geometry was used to characterize the titanium alloys properties from the point of view of the forming zone and titanium structure effect. The structure and properties of the materials were assessed by means of metallographic analyses and microhardness measurements.The highest differences in the parameters assessed as a function of the sampling zone were observed in the case of alpha-phase Ti-Gr2at the expense of the most substantial sheet thinning occurrence. A springback causes a smaller stored deformation in Timetal (β alloy) resulting in less pronounced microstructure refinement and microhardness increase. Ti-6Al-4V alloy exhibited early failure due to its poor formability at ambient temperature.

 

Keywords: Incremental forming, metallography, hardness, titanium alloys.

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Authors: D. Sivakumar

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The groundwater quality was assessed nearby places of Nagalkeni, Chennai, Tamil Nadu, India. The selected physico-chemical parameters were pH, EC, TDS, total hardness (TH), anions like Ca, Mg, Na and K, and cations like SO₄, NO_3, Cl_2, HCO₃, and CO₃, and Cr(VI). In order to suit the groundwater for drinking and irrigation purposes, compared the value of selected parameters with the value of selected parameters from BIS drinking water quality standard and irrigation water quality indices. The physico-chemical study of the groundwater systems of selected sites of nearby places of Nagalkeni showed that the groundwater is nearly acidic and mostly oxidizing in nature and hence, water is not suitable for drinking purpose directly. The results of the irrigation indices indicated that the groundwater samples in the study area found to be brackish water, results, groundwater from the study area is also not suitable for irrigation purpose directly, but the groundwater may be used after implementing some suitable treatment techniques.

Keywords: Physico-Chemical Parameters, Tannery Industry Effluent, Groundwater Quality Indices.

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Authors: H. Erbiyik, A. Bal, M. Sirakaya, Ö. Yesildal, E. Yolcu

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The emergence of many environmental issues began with the Industrial Revolution. The depletion of natural resources and emerging environmental challenges over time requires enterprises and managers to take into consideration environmental factors while managing business. If we take notice of these causes; the design and implementation of environmentally friendly green purchasing, production and waste management systems become very important at green logistics systems. Companies can adopt green supply chain with the awareness of these facts. The concept of green supply chain constitutes from green purchasing, green production, green logistics, waste management and reverse logistics. In this study, we wanted to identify the concept of green supply chain and why green supply chain should be applied. In the practice part of the study an analytic hierarchy process (AHP) study is conducted on an aluminum production company to evaluate suppliers.

Keywords: Aluminum sector, analytic hierarchy process, decision making, green logistics.

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Authors: I. Markovska, F. Yovkova, G. Minov, D. Rusev, L. Lyubchev

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The present research focus on the processing of mullite-based ceramics from oil refinery industrial wastes and byproducts of agricultural industry and on the investigating of silane modified surface of ceramics. Two waste products were used as initial material – waste aluminum oxide and waste rice husk. The burning - out additives used were waste rise husk. It is known that  the oxide ceramics surface is hydrophilic due to the presence of – OH groups in it. The nature of ceramic surface regarding permeation of water and hydrocarbons can be changed by further treatment with silanes. The samples were studied mainly by X-ray analysis, FT-IR absorbance measurements and microscopic analysis. The X-ray analyses showed the phase composition depends on the firing temperature and on the purity of the starting alumina. Two kind of silanes were used for the transformation of surface from hydrophilic to hydrophobic – trimethoxymethylsilane (TMMS) and trimethylclorsilane (TMCS).

Keywords: Porous mullite ceramics, waste materials, trimethoxymethylsilane, trimethylclorsilane.

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Authors: Le Ngoc Hung, Abriak Nor Edine, Binetruy Christophe, Benzerzour Mahfoud, Shahrour Isam, Patrice Rivard

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Bottom ash from Municipal Solid Waste Incineration (MSWI) can be viewed as a typical granular material because these industrial by-products result from the incineration of various domestic wastes. MSWI bottom ash is mainly used in road engineering in substitution of the traditional natural aggregates. As the characterization of their mechanical behavior is essential in order to use them, specific studies have been led over the past few years. In the first part of this paper, the mechanical behavior of MSWI bottom ash is studied with triaxial tests. After, analysis of the experiment results, the simulation of triaxial tests is carried out by using the software package CESAR-LCPC. As the first approach in modeling of this new class material, the Mohr-Coulomb model was chosen to describe the evolution of material under the influence of external mechanical actions.

Keywords: Bottom ash, granular material, triaxial test, mechanical behavior, simulation, Mohr-Coulomb model, CESARLCPC.

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Authors: Li Xu, Huanbao Jiang, Zhenfei Huang, Lailai Zhang

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In recent years, as global warming, the sea-ice extent of North Arctic undergoes an evident decrease and Arctic channel has attracted the attention of shipping industry. Ice crystals existing in the seawater of Arctic channel which enter the seawater system of the ship with the seawater were found blocking the seawater pipe. The appearance of cooler paralysis, auxiliary machine error and even ship power system paralysis may be happened if seriously. In order to reduce the effect of high temperature in auxiliary equipment, seawater system will use external ice-water to participate in the cooling cycle and achieve the state of its flow. The distribution of ice crystals in seawater pipe can be achieved. As the ice slurry system is solid liquid two-phase system, the flow process of ice-water mixture is very complex and diverse. In this paper, the flow process in seawater pipe of ice slurry is simulated with fluid dynamics simulation software based on k-ε turbulence model. As the ice packing fraction is a key factor effecting the distribution of ice crystals, the influence of ice packing fraction on the flowing process of ice slurry is analyzed. In this work, the simulation results show that as the ice packing fraction is relatively large, the distribution of ice crystals is uneven in the flowing process of the seawater which has such disadvantage as increase the possibility of blocking, that will provide scientific forecasting methods for the forming of ice block in seawater piping system. It has important significance for the reliability of the operating of polar ships in the future.

Keywords: Ice slurry, seawater pipe, ice packing fraction, numerical simulation.

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in Service Level Agreements (SLAs), Customer Relationship Management (CRM) relations, trends and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: Cybersecurity, critical infrastructure, smart industries, digital platform.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Hakim Aguedal, Hafida Hentit, Abdallah Aziz, Djillali Rida Merouani, Abdelkader Iddou

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The major environmental risk of soil pollution is the contamination of groundwater by infiltration of organic and inorganic pollutants which can cause a serious menace. To prevent this risk and to protect the groundwater, we proceeded in this study to test the reliability of a biosolid as barrier to prevent the migration of very dangerous pollutants as ‘Cadmium’ through the different soil layers. In this study, we tried to highlight the effect of several parameters such as: turbidity (different cycle of Hydration/Dehydration), rainfall, effect of initial Cd(II) concentration and the type of soil. These parameters allow us to find the most effective manner to integrate this barrier in the soil. From the results obtained, we found a significant effect of the barrier. Indeed, the recorded passing quantities are lowest for the highest rainfall; we noted also that the barrier has a better affinity towards higher concentrations; the most retained amounts of cadmium has been in the top layer of the two types of soil tested, while the lowest amounts of cadmium are recorded in the bottom layers of soils.

Keywords: Adsorption of Cadmium, Barrier, Groundwater Pollution, Protection.

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Authors: Rahim Sotoudeh Bahreini, Alireza Foroughi Nematollahi, Akbar Jafari

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This study investigates the mechanism of a Gyratory crusher-located in Golgohar mining and industrial Co. specifically with a focus on stresses distribution and fatigue failure of its main shaft. At first step, the cross section of the fractured shaft is studied, and the crack growth is analyzed. Then, the rotational motion of the shaft and the oil temperature of oil circuit of equipment are monitored. Condition monitoring is used to help finding a better modification. Based on the results of this study, the main causes of shaft failure are identified, and corrective solution is offered to increase crusher performance, especially its main shaft life. To predict the efficiency of the proposed modification, finite element simulation is performed, and its results are compared with the similar modified cases. The comparison and interpretation of simulation results confirm the efficiency of proposed corrective method.

Keywords: Fatigue failure, finite element method, gyratory crusher, condition monitoring.

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Authors: Jalil Emadi, Masoud Nasri, Ali Najafi, Yousef Moradi Shahgharyeh

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Development of cities and villages, agricultural farms and industrial regions in abutment and/or in the course of streams and rivers or in prone flood lands has been caused more notations in hydrology problems and city planning topics. In order to protection of cities against of flood damages, embankment construction is a desired and scientific method. The cities that located in arid zones may damage by floods periodically. Zavvareh city in Ardestan township(Isfahan province) with 7704 people located in Ardestan plain that has been damaged by floods that have flowed from dominant mountainous watersheds in past years with regard to return period. In this study, according to flowed floods toward Zavvareh city, was attempt to plan suitable hydraulic structures such as canals, bridges and collectors in order to collection, conduction and depletion of city surface runoff.

Keywords: Flood, flood way, executive consideration, embankment, surface runoff network, Zavvareh.

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Authors: A. O. Ogunlela, B. Adelodun

Abstract:

Flood routing is used in estimating the travel time and attenuation of flood waves as they move downstream a river or channel. The routing procedure is usually classified as hydrologic or hydraulic. Hydraulic methods utilize the equations of continuity and motion. Kinematic routing, a hydraulic technique was used in routing Asa River at Ilorin. The river is of agricultural and industrial importance to Ilorin, the capital of Kwara State, Nigeria. This paper determines the kinematic parameters of kinematic wave velocity, time step, time required to traverse, weighting factor and change in length. Values obtained were 4.67 m/s, 19 secs, 21 secs, 0.75 and 100 m, respectively. These parameters adequately reflect the watershed and flow characteristics essential for the routing. The synthetic unit hydrograph was developed using the Natural Resources Conservation Service (NRCS) method. 24-hr 10yr, 25yr, 50yr and 100yr storm hydrographs were developed from the unit hydrograph using convolution procedures and the outflow hydrographs were obtained for each of 24-hr 10yr, 25yr, 50yr and 100yr indicating 0.11 m³/s, 0.10 m³/s, 0.10 m³/s and 0.10 m³/s attenuations respectively.

Keywords: Asa River, Kinematic parameters, Routing

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Authors: Hojjat Saberinejad, Adel Hashiehbaf, Ehsan Afrasiabian

Abstract:

Among the various cooling processes in industrial applications such as: electronic devices, heat exchangers, gas turbines, etc. Gas turbine blades cooling is the most challenging one. One of the most common practices is using ribbed wall because of the boundary layer excitation and therefore making the ultimate cooling. Vortex formation between rib and channel wall will result in a complicated behavior of flow regime. At the other hand, selecting the most efficient method for capturing the best results comparing to experimental works would be a fascinating issue. In this paper 4 common methods in turbulence modeling: standard k-e, rationalized k-e with enhanced wall boundary layer treatment, k-w and RSM (Reynolds stress model) are employed to a square ribbed channel to investigate the separation and thermal behavior of the flow in the channel. Finally all results from different methods which are used in this paper will be compared with experimental data available in literature to ensure the numerical method accuracy.

Keywords: boundary layer, turbulence, numerical method, rib cooling

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

Abstract:

Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: Rotating shaft, flexible blades, centrifugal stiffening, stability.

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Authors: Rouzbeh Shafaghat, Hoda Shafaghat, Fatemeh Ghanbari, Pouya Sirous Rezaei, Rohollah Espanani

Abstract:

Nowadays, desalination of salt water is considered an important industrial process. In many parts of the world, particularly in the gulf countries, the multi-stage flash (MSF) water desalination has an essential contribution in the production of fresh water. In this study, a simple mathematical model is defined to design a MSF desalination system and the feasibility of using the MSF desalination process in proximity of a 42 MW power plant is investigated. This power plant can just provide 10 ton/h superheated steam from low pressure (LP) section of heat recovery steam generator (HRSG) for thermal desalting system. The designed MSF system with gained output ratio (GOR) of 10.3 has 24 flashing stages and can produce 2480 ton/d of fresh water. The expected performance characteristics of the designed MSF desalination plant are determined. In addition, the effect of motive water pressure on the amount of non-condensable gases removed by water jet vacuum pumps is investigated.

Keywords: Design, dual-purpose power plant, mathematical model, MSF desalination.

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