Search results for: Thermal Machine

Authors: S. Ben Saad, F. Ayad, H. Damotte

Abstract:

This study deals with Computational Fluid Dynamics (CFD) studies of the interactions between the air flow and louvered fins which equipped the automotive heat exchangers. 3D numerical simulation results are obtained by using the ANSYS Fluent 13.0 code and compared to experimental data. The paper studies the effect of louver angle and louver pitch geometrical parameters, on overall thermal hydraulic performances of louvered fins. The comparison between CFD simulations and experimental data show that established 3-D CFD model gives a good agreement. The validation agrees, with about 7% of deviation respectively of friction and Colburn factors to experimental results. As first, it is found that the louver angle has a strong influence on the heat transfer rate. Then, louver angle and louver pitch variation of the louvers and their effects on thermal hydraulic performances are studied. In addition to this study, it is shown that the second half of the fin takes has a significant contribution on pressure drop increase without any increase in heat transfer.

Keywords: CFD simulations, automotive heat exchanger, performances.

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: Central ML, embedded machine learning, energy consumption, local ML, Wireless Sensor Networks, WSN.

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Authors: R. Knizek, D. Karhankova

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The production of nanofibers and the machinery for their production is a current issue. The pioneer, in the industrial production of nanofibers, is the machinery with the sales descriptions Nanospider^TM from the company Elmarco, which came into being in 2008. Most of the production facilities, like Nanospider^TM, use electrospinning. There are also other methods of industrial production of nanofibers, such as the centrifugal spinning process, which is used by FibeRio Technology Corporation. However, each method and machine has its advantages, but also disadvantages and that is the reason why a new machine called as Nanomachine, which eliminates the disadvantages of other production facilities producing nanofibers, has been developed.

Keywords: Nanomachine, nanospider, spinning slat, electrospinning.

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Authors: Allagui Hatem, Ghodbane Fathi

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The primary objective of this paper is to study the thermal effects of the electric arc on the breaker apparatus contacts for forecasting and improving the contact durability. We will propose a model which takes account of the main influence factors on the erosion contacts. This phenomenon is very complicated because the amount of ejected metal is not necessarily constituted by the whole melted metal bath but this depends on the balance of forces on the contact surface. Consequently, to calculate the metal ejection coefficient, we propose a method which consists in comparing the experimental results with the calculated ones. The proposed model estimates the mass lost by vaporization, by droplets ejection and by the extraction mechanism of liquid or solid metal. In the one-dimensional geometry, to calculate of the contact heating, we used Green’s function which expresses the point source and allows the transition to the surface source. However, for the two- dimensional model we used explicit and implicit numerical methods. The results are similar to those found by Wilson’s experiments.

Keywords: Electric arc, thermal effect, erosion, contact, durability.

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Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

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Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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Authors: Abdallah M. Abualkishik, Khairuddin Omar

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This article concerned with the translation of Quranic verses to Braille symbols, by using Visual basic program. The system has the ability to translate the special vibration for the Quran. This study limited for the (Noun + Scoon) vibrations. It builds on an existing translation system that combines a finite state machine with left and right context matching and a set of translation rules. This allows to translate the Arabic language from text to Braille symbols after detect the vibration for the Quran verses.

Keywords: Braille, Quran vibration, Finite State Machine.

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Authors: V. Koci, J. Madera, R. Cerny

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Calculations of energy efficiency of several AACbased building envelopes under different climatic conditions are presented. As thermal insulating materials, expanded polystyrene and hydrophobic and hydrophilic mineral wools are assumed. The computations are accomplished using computer code HEMOT developed at Department of Materials Engineering, Faculty of Civil Engineering at the Czech Technical University in Prague. The climatic data of Athens, Kazan, Oslo, Prague and Reykjavík are obtained using METEONORM software.

Keywords: climatic conditions, computational simulation, energy efficiency, thermal insulation

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts.

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Authors: Maged A. Mossallam

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The objective from this paper is to design a solar thermal engine for space vehicles orbital control and electricity generation. A computational model is developed for the prediction of the solar thermal engine performance for different design parameters and conditions in order to enhance the engine efficiency. The engine is divided into two main subsystems. First, the concentrator dish which receives solar energy from the sun and reflects them to the cavity receiver. The second one is the cavity receiver which receives the heat flux reflected from the concentrator and transfers heat to the fluid passing over. Other subsystems depend on the application required from the engine. For thrust application, a nozzle is introduced to the system for the fluid to expand and produce thrust. Hydrogen is preferred as a working fluid in the thruster application. Results model developed is used to determine the thrust for a concentrator dish 4 meters in diameter (provides 10 kW of energy), focusing solar energy to a 10 cm aperture diameter cavity receiver. The cavity receiver outer length is 50 cm and the internal cavity is 47 cm in length. The suggested design material of the internal cavity is tungsten to withstand high temperature. The thermal model and analysis shows that the hydrogen temperature at the plenum reaches 2000oK after about 250 seconds for hot start operation for a flow rate of 0.1 g/sec.Using solar thermal engine as an electricity generation device on earth is also discussed. In this case a compressor and turbine are used to convert the heat gained by the working fluid (air) into mechanical power. This mechanical power can be converted into electrical power by using a generator.

Keywords: Concentrated Solar Energy, Orbital Control, Power Generation, Solar Thermal Engine, Space Vehicles Propulsion

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Authors: Yu-Wei Chang, Chiao-Hung Cheng, Wen-Fang Wu, Sih-Li Chen

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This article experimentally investigates the thermal performance of thermoelectric air-cooling module which comprises a thermoelectric cooler (TEC) and an air-cooling heat sink. The influences of input current and heat load are determined. And performances under each situation are quantified by thermal resistance analysis. Since TEC generates Joule heat, this nature makes construction of thermal resistance network difficult. To simplify the analysis, this article emphasizes on the resistance heat load might meet when passing through the device. Therefore, the thermal resistances in this paper are to divide temperature differences by heat load. According to the result, there exists an optimum input current under every heating power. In this case, the optimum input current is around 6A or 7A. The performance of the heat sink would be improved with TEC under certain heating power and input current, especially at a low heat load. According to the result, the device can even make the heat source cooler than the ambient. However, TEC is not always effective at every heat load and input current. In some situation, the device works worse than the heat sink without TEC. To determine the availability of TEC, this study figures out the effective operating region in which the TEC air-cooling module works better than the heat sink without TEC. The result shows that TEC is more effective at a lower heat load. If heat load is too high, heat sink with TEC will perform worse than without TEC. The limit of this device is 57W. Besides, TEC is not helpful if input current is too high or too low. There is an effective range of input current, and the range becomes narrower when the heat load grows.

Keywords: Thermoelectric cooler, TEC, electronic cooling, heat sink.

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Authors: A. Ashjaran, A. Rashidi, R. Ghazi-Saeidi

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Protective clothing limits heat transfer and hampers task performance due to the increased weight. Militarism protective clothing enables humans to operate in adverse environments. In the selection and evaluation of militarism protective clothing attention should be given to heat strain, ergonomic and fit issues next to the actual protection it offers. Fifty Male healthy subjects participated in the study. The subjects were dressed in shorts, T-shirts, socks, sneakers and four deferent kinds of militarism protective clothing such as CS, CSB, CS with NBC protection and CS with NBC- protection added. Ergonomically and psychological strains of every four cloths were investigated on subjects by walking on a treadmill (7km/hour) with a 19.7 kg backpack. As a result of these tests were showed that, the highest heart rate was found wearing the NBC-protection added outfit, the highest temperatures were observed wearing NBCprotection added, followed by respectively CS with NBC protection, CSB and CS and the highest value for thermal comfort (implying worst thermal comfort) was observed wearing NBC-protection added.

Keywords: Militarist protective clothing, Ergonomic, Heat strain, Thermal comfort

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

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Authors: Rossitza M. Setchi, Qiao Tang

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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Keywords: Concepts, indexing, machine learning, ontology, tagging.

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Authors: Ramy H. Mohammed

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Understanding the behavior of airflow in a room is essential for building designers to provide the most efficient design of ventilation system, and having acceptable indoor air quality. This trend is the motive to solve the relationship between airflow parameters and thermal comfort. This paper investigates airflow characteristics, indoor air quality (IAQ), and the thermal comfort (TC) in a ventilated room with a displacement ventilation system using three dimensional CFD code [AirPak 2.0.6]. After validation of the code, a numerical study is executed for a typical room with dimensions of 5m by 3m by 3m height according to a variety of supply air velocities, supply air temperature and supply air relative humidity. The finite volume method and the indoor zero equation turbulence models are employed for solving the governing equations numerically. The temperature field and the mean age of air (MAA) in the modeled room for a displacement ventilation system are determined according to a variety of the above parameters. The variable air volume (VAV) systems with different supply air velocity are applicable to control room air temperature for a displacement ventilation system.

Keywords: Displacement ventilation, AirPak, Indoor zero equation, MAA.

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.

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Authors: K. Freedman

Abstract:

In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity. These same results were found in psychiatric studies of human character recognition.

Keywords: Character recognition, cognitive model, support vector machine learning.

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Authors: Huei Chu Weng

Abstract:

This paper presents a study on the effect of second-order slip on forced convection through a long isoflux heated or cooled planar microchannel. The fully developed solutions of flow and thermal fields are analytically obtained on the basis of the second-order Maxwell-Burnett slip and local heat flux boundary conditions. Results reveal that when the average flow velocity increases or the wall heat flux amount decreases, the role of thermal creep becomes more insignificant, while the effect of second-order slip becomes larger. The second-order term in the Deissler slip boundary condition is found to contribute a positive velocity slip and then to lead to a lower pressure drop as well as a lower temperature rise for the heated-wall case or to a higher temperature rise for the cooled-wall case. These findings are contrary to predictions made by the Karniadakis slip model.

Keywords: Microfluidics, forced convection, thermal creep, second-order boundary conditions.

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Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami

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Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.

Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.

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Authors: Yasar Bicer, Serif Yilmaz

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In present study, two kinds of thermal power plant ashes; one the fly ash and the other waste ash are mixed with adhesive tragacanth and cement to produce new composite materials. 48 new samples are produced by varying the percentages of the fly ash, waste ash, cement and tragacanth. The new samples are subjected to some tests to find out their properties such as thermal conductivity, compressive strength, tensile strength and sucking capability of water. It is found that; the thermal conductivity decreases with increasing amount of tragacanth in the mixture. The compressive, tensile strength increases when the rate of tragacanth is up to 1%, whilst as the amount of tragacanth increases up to 1.5%, the compressive, tensile strength decreases slightly. The rate of water absorption of samples was more than 30%. From this result, it is concluded that these materials can not be used as external plaster or internal plaster material that faces to water. They can be used in internal plaster unless touching water and they can be used as cover plaster under roof and riprap material in sandwich panels. It is also found that, these materials can be cut with saw, drilled with screw and painted with any kind of paint.

Keywords: Fly ash, tragacanth, cement, composite material.

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Authors: Sarka Keprdova, Jiri Bydzovsky

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This article describes to what extent the addition of energy by-products into the structures of the technical hemp filling materials influence their properties. The article focuses on the changes in physical-mechanical and thermal technical properties of materials after the addition of ash or FBC ash or slag in the binding component of material. Technical hemp filling materials are made of technical hemp shives bonded by the mixture of cement and dry hydrate lime. They are applicable as fillers of vertical or horizontal structures or roofs. The research used eight types of energy by-products of power or heating plants in the Czech Republic. Secondary energy products were dispensed in three different percentage ratios as a replacement of cement in the binding component. Density, compressive strength and determination of the coefficient of thermal conductivity after 28, 60 and 90 days of curing in a laboratory environment were determined and subsequently evaluated on the specimens produced.

Keywords: Ash, binder, cement, energy by-product, FBC ash (fluidized bed combustion ash), filling materials, shives, slag, technical hemp.

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Authors: Govindaraju.M, Ganeshkumar.R.S, Suganthi.P, Muthukumaran.V.R, Visvanathan.P

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The present study was conducted to investigate the response of plants exposed to lignite-based thermal power plant emission. For this purpose, five plant species were collected from 1.0 km distance (polluted site) and control plants were collected from 20.0 km distance (control site) to thermal power plant. The common tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn, Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus religiosa L. were selected as test plants. Photosynthetic pigments changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco enzyme modifications were studied. Reduction was observed in the photosynthetic pigments of plants growing in polluted site and also large sub unit of the rubisco enzyme was degraded in Azadirachta indica A. Juss collected from polluted site.

Keywords: Air pollution, Lignite-based thermal power plant, Photosynthetic pigments, Rubisco enzyme.

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Authors: Jan Pomikalek, Radim Rehurek

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Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.

Keywords: Text categorization, machine learning, electronic documents, classification.

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Authors: A. Almasi

Abstract:

Reciprocating compressors are flexible to handle wide capacity and condition swings, offer a very efficient method of compressing almost any gas mixture in wide range of pressure, can generate high head independent of density, and have numerous applications and wide power ratings. These make them vital component in various units of industrial plants. In this paper optimum reciprocating compressor configuration regarding interstage pressures, low suction pressure, non-lubricated cylinder, speed of machine, capacity control system, compressor valve, lubrication system, piston rod coating, cylinder liner material, barring device, pressure drops, rod load, pin reversal, discharge temperature, cylinder coolant system, performance, flow, coupling, special tools, condition monitoring (including vibration, thermal and rod drop monitoring), commercial points, delivery and acoustic conditions are presented.

Keywords: Design, optimum, reciprocating compressor.

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Authors: P. Niranatlumpong, H. Koiprasert, C. Sukhonket, K. Ninon, N. Coompreedee

Abstract:

The use of a conventional air plasma-sprayed thermal barrier coating (TBC) and a porous, functionally graded TBC as a thermal insulator for Al7075 alloy was explored. A quench test at 1200°C employing fast heating and cooling rates was setup to represent a dynamic thermal condition of an aerospace component. During the test, coated samples were subjected the ambient temperature of 1200°C for a very short time. This was followed by a rapid drop in temperature resulting in cracking of the coatings. For the conventional TBC, it was found that the temperature of the Al7075 substrate decreases with the increase in the ZrO₂ topcoat thickness. However, at the topcoat thickness of 1100 µm, large horizontal cracks can be observed in the topcoat and at the topcoat thickness of 1600 µm, the topcoat delaminate during cooling after the quench test. The porous, functionally graded TBC with 600 µm thick topcoat, on the other hand, was found to be as effective at reducing the substrate temperature as the conventional TBC with 1100 µm thick topcoat. The maximum substrate temperature is about 213°C for the former and 208°C for the latter when a heating rate of 38°C/s was used. When the quench tests were conducted with a faster heating rate of 128°C/s, the Al7075 substrate heat up faster with a reduction in the maximum substrate temperatures. The substrate temperatures dropped from 297 to 212°C for the conventional TBC and from 213 to 155°C for the porous TBC, both with 600 µm thick topcoat. Segmentation cracks were observed in both coating after the quench test.

Keywords: Thermal barrier coating, Al7075, porous TBC, Quenching.

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Authors: Kyoung Hoon Kim

Abstract:

Recently ORC(Organic Rankine Cycle) has attracted much attention due to its potential in reducing consumption of fossil fuels and its favorable characteristics to exploit low-grade heat sources. In this work thermodynamic performance of ORC with superheating of vapor is comparatively assessed for various working fluids. Special attention is paid to the effects of system parameters such as the evaporating temperature and the turbine inlet temperature on the characteristics of the system such as maximum possible work extraction from the given source, volumetric flow rate per 1 kW of net work and quality of the working fluid at turbine exit as well as thermal and exergy efficiencies. Results show that for a given source the thermal efficiency increases with decrease of the superheating but exergy efficiency may have a maximum value with respect to the superheating of the working fluid. Results also show that in selection of working fluid it is required to consider various criteria of performance characteristics as well as thermal efficiency.

Keywords: organic Rankine cycle (ORC), low-grade energysource, Patel-Teja equation, thermodynamic performance

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Authors: Jehnming Lin

Abstract:

The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constrains. Therefore the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: Laser cleavage, controlled fracture, contact ball lens.

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Authors: Mohd A. Mezher, Maysam F. Abbod

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Genetic Folding (GF) a new class of EA named as is introduced for the first time. It is based on chromosomes composed of floating genes structurally organized in a parent form and separated by dots. Although, the genotype/phenotype system of GF generates a kernel expression, which is the objective function of superior classifier. In this work the question of the satisfying mapping-s rules in evolving populations is addressed by analyzing populations undergoing either Mercer-s or none Mercer-s rule. The results presented here show that populations undergoing Mercer-s rules improve practically models selection of Support Vector Machine (SVM). The experiment is trained multi-classification problem and tested on nonlinear Ionosphere dataset. The target of this paper is to answer the question of evolving Mercer-s rule in SVM addressed using either genetic folding satisfied kernel-s rules or not applied to complicated domains and problems.

Keywords: Genetic Folding, GF, Evolutionary Algorithms, Support Vector Machine, Genetic Algorithm, Genetic Programming, Multi-Classification, Mercer's Rules

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.

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Authors: E. H. N. Gashti, M. Malaska, K. Kujala

Abstract:

The thermo-mechanical behaviour of concrete energy pile foundations with different single and double U-tube shapes incorporated was analysed using the Comsol Multi-physics package. For the analysis, a 3D numerical model in real scale of the concrete pile and surrounding soil was simulated regarding actual operation of ground heat exchangers (GHE) and the surrounding ambient temperature. Based on initial ground temperature profile measured in situ, tube inlet temperature was considered to range from 6oC to 0oC (during the contraction process) over a 30-day period. Extra thermal stresses and deformations were calculated during the simulations and differences arising from the use of two different systems (single-tube and double-tube) were analysed. The results revealed no significant difference for extra thermal stresses at the centre of the pile in either system. However, displacements over the pile length were found to be up to 1.5-fold higher in the double-tube system than the singletube system.

Keywords: Concrete Energy Piles, Stresses, Displacements, Thermo-mechanical behaviour, Soil-structure interactions.

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Authors: Marianna I. Triantou, Konstantina I. Stathi, Petroula A. Tarantili

Abstract:

In the present study, the incorporation of graphene into blends of acrylonitrile-butadiene-styrene terpolymer with polypropylene (ABS/PP) was investigated focusing on the improvement of their thermomechanical characteristics and the effect on their rheological behavior. The blends were prepared by melt mixing in a twin-screw extruder and were characterized by measuring the MFI as well as by performing DSC, TGA and mechanical tests. The addition of graphene to ABS/PP blends tends to increase their melt viscosity, due to the confinement of polymer chains motion. Also, graphene causes an increment of the crystallization temperature (Tc), especially in blends with higher PP content, because of the reduction of surface energy of PP nucleation, which is a consequence of the attachment of PP chains to the surface of graphene through the intermolecular CH-π interaction. Moreover, the above nanofiller improves the thermal stability of PP and increases the residue of thermal degradation at all the investigated compositions of blends, due to the thermal isolation effect and the mass transport barrier effect. Regarding the mechanical properties, the addition of graphene improves the elastic modulus, because of its intrinsic mechanical characteristics and its rigidity, and this effect is particularly strong in the case of pure PP.

Keywords: Acrylonitrile-butadiene-styrene terpolymer, blends, graphene, polypropylene.

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