Search results for: thermal cycling machine

Authors: Madhu Aneja, Sapna Sharma

Abstract:

Thermal conductivity of ordinary heat transfer fluids is not adequate to meet today’s cooling rate requirements. Nanoparticles have been shown to increase the thermal conductivity and convective heat transfer to the base fluids. One of the possible mechanisms for anomalous increase in the thermal conductivity of nanofluids is the Brownian motions of the nanoparticles in the basefluid. In this paper, the natural convection of incompressible nanofluid over a nonlinear stretching sheet in the presence of magnetic field is studied. The flow and heat transfer induced by stretching sheets is important in the study of extrusion processes and is a subject of considerable interest in the contemporary literature. Appropriate similarity variables are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary (similarity) differential equations. For computational purpose, Finite Element Method is used. The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo – Klienstreuer – Li) correlation. In this model effect of Brownian motion on thermal conductivity is considered. The effect of important parameter i.e. nonlinear parameter, volume fraction, Hartmann number, heat source parameter is studied on velocity and temperature. Skin friction and heat transfer coefficients are also calculated for concerned parameters.

Keywords: Brownian motion, convection, finite element method, magnetic field, nanofluid, stretching sheet

Procedia PDF Downloads 204

Authors: Thomas Merciris, Mathieu Masquere, Yann Cressault, Pascale Petit

Abstract:

The goal of an alternative current (AC) switching device is to allow the arc (created during the opening phase of the contacts) to extinguish at the current zero. The plasma temperature rate of cooling down, the electrical characteristic of the arc (current-voltage), and the rise rate of the transient recovery voltage (TRV) are critical parameters which influence the performance of a switching device. To simulate the thermal extinction of the arc and to obtain qualitative data on the processes responsible for this phenomenon, a 1D MHD fluid model in the air was developed and coupled to an external electric circuit. After thermal extinction, the dielectric strength of the hot air (< 4kK) was then estimated by the Bolsig+ software and the critical electric fields method with the temperature obtained by the MHD simulation. The influence of copper Cu and silver Ag vapors was investigated on the thermal and dielectric part of the simulation with various current forms (100A to 1kA). Finally, those values of dielectric strength have been compared to the experimental values obtained in the case of two separating silver contacts. The preliminary results seem to indicate the dielectric strength after multiples hundreds of microseconds is the same order of magnitude as experimentally found.

Keywords: MHD simulation, dielectric recovery, Bolsig+, silver vapors, copper vapors, breakers, electric arc

Procedia PDF Downloads 97

Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

Abstract:

The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

Procedia PDF Downloads 357

Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

Abstract:

Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

Procedia PDF Downloads 137

Authors: Ammar Alsabery, Habibis Saleh, Norazam Arbin, Ishak Hashim

Abstract:

Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal non-equilibrium model is studied in this paper. The left vertical wall is maintained at a constant hot temperature and the right vertical wall is maintained at a constant cold temperature, while the horizontal walls are adiabatic. The governing equations are obtained by applying the Darcy model and Boussinesq approximation. COMSOL's finite element method is used to solve the non-dimensional governing equations together with specified boundary conditions. The governing parameters of this study are the Rayleigh number, the modified thermal conductivity ratio, the inter-phase heat transfer coefficien and the time independent. The results presented for values of the governing parameters in terms of streamlines in both fluid/porous layer, isotherms of fluid and solid porous layer, isotherms of fluid layer, and average Nusselt number.

Keywords: unsteady natural convection, thermal non-equilibrium model, Darcy model

Procedia PDF Downloads 369

Authors: Huseyin A. Yavasoglu, Yusuf Ziya Tengiz, Ali Göksenli

Abstract:

In this study, an automatic feeding machine for different type and class of bovine animals is designed. Daily nutrition of a bovine consists of grass, corn, straw, silage, oat, wheat and different vitamins and minerals. The amount and mixture amount of each of the nutrition depends on different parameters of the bovine. These parameters are; age, sex, weight and maternity of the bovine, also outside temperature. The problem in a farm is to constitute the correct mixture and amount of nutrition for each animal. Faulty nutrition will cause an insufficient feeding of the animal concluding in an unhealthy bovine. To solve this problem, a new automatic feeding machine is designed. Travelling of the machine is performed by four tires, which is pulled by a tractor. The carrier consists of eight bins, which each of them carries a nutrition type. Capacity of each unit is 250 kg. At the bottom of each chamber is a sensor measuring the weight of the food inside. A funnel is at the bottom of each chamber by which open/close function is controlled by a valve. Each animal will carry a RFID tag including ID on its ear. A receiver on the feeding machine will read this ID and by given previous information by the operator (veterinarian), the system will detect the amount of each nutrition unit which will be given to the selected animal for feeding. In the system, each bin will open its exit gate by the help of the valve under the control of PLC (Programmable Logic Controller). The amount of each nutrition type will be controlled by measuring the open/close time. The exit canals of the bins are collected in a reservoir. To achieve a homogenous nitration, the collected feed will be mixed by a worm gear. Further the mixture will be transported by a help of a funnel to the feeding unit of the animal. The feeding process can be performed in 100 seconds. After feeding of the animal, the tractor pulls the travelling machine to the next animal. By the help of this system animals can be feeded by right amount and mixture of nutrition

Keywords: bovine, feeding, nutrition, transportation, automatic

Procedia PDF Downloads 334

Authors: Evy Van Puymbroeck, Wim Nagy, Ken Schotte, Heng Fang, Hans De Backer

Abstract:

The knowledge of residual stresses for welded bridge components is essential to determine the effect of the residual stresses on the fatigue life behavior. The residual stresses of an orthotropic bridge deck are determined by simulating the welding process with finite element modelling. The stiffener is placed on top of the deck plate before welding. A chained thermal-mechanical analysis is set up to determine the distribution of residual stresses for the bridge deck. First, a thermal analysis is used to determine the temperatures of the orthotropic deck for different time steps during the welding process. Twin wire submerged arc welding is used to construct the orthotropic plate. A double ellipsoidal volume heat source model is used to describe the heat flow through a material for a moving heat source. The heat input is used to determine the heat flux which is applied as a thermal load during the thermal analysis. The heat flux for each element is calculated for different time steps to simulate the passage of the welding torch with the considered welding speed. This results in a time dependent heat flux that is applied as a thermal loading. Thermal material behavior is specified by assigning the properties of the material in function of the high temperatures during welding. Isotropic hardening behavior is included in the model. The thermal analysis simulates the heat introduced in the two plates of the orthotropic deck and calculates the temperatures during the welding process. After the calculation of the temperatures introduced during the welding process in the thermal analysis, a subsequent mechanical analysis is performed. For the boundary conditions of the mechanical analysis, the actual welding conditions are considered. Before welding, the stiffener is connected to the deck plate by using tack welds. These tack welds are implemented in the model. The deck plate is allowed to expand freely in an upwards direction while it rests on a firm and flat surface. This behavior is modelled by using grounded springs. Furthermore, symmetry points and lines are used to prevent the model to move freely in other directions. In the thermal analysis, a mechanical material model is used. The calculated temperatures during the thermal analysis are introduced during the mechanical analysis as a time dependent load. The connection of the elements of the two plates in the fusion zone is realized with a glued connection which is activated when the welding temperature is reached. The mechanical analysis results in a distribution of the residual stresses. The distribution of the residual stresses of the orthotropic bridge deck is compared with results from literature. Literature proposes uniform tensile yield stresses in the weld while the finite element modelling showed tensile yield stresses at a short distance from the weld root or the weld toe. The chained thermal-mechanical analysis results in a distribution of residual weld stresses for an orthotropic bridge deck. In future research, the effect of these residual stresses on the fatigue life behavior of welded bridge components can be studied.

Keywords: finite element modelling, residual stresses, thermal-mechanical analysis, welding simulation

Procedia PDF Downloads 165

Authors: Long Kim Vu

Abstract:

The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

Procedia PDF Downloads 173

Authors: Prashant Verma

Abstract:

Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

Procedia PDF Downloads 129

Authors: Marianna I. Triantou, Petroula A. Tarantili

Abstract:

In this research work, poly (acrylonitrile-butadiene-styrene)/polypropylene (ABS/PP) blends were processed by melt compounding in a twin-screw extruder. Upgrading of the thermal characteristics of the obtained materials was attempted by the incorporation of organically modified montmorillonite (OMMT), as well as, by the addition of two types of compatibilizers; polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS grafted with maleic anhydride (ABS-g-MAH). The effect of the above treatments was investigated separately and in combination. Increasing the PP content in ABS matrix seems to increase the thermal stability of their blend and the glass transition temperature (Tg) of SAN phase of ABS. From the other part, the addition of ABS to PP promotes the formation of its β-phase, which is maximum at 30 wt% ABS concentration, and increases the crystallization temperature (Tc) of PP. In addition, it increases the crystallization rate of PP.The β-phase of PP in ABS/PP blends is reduced by the addition of compatibilizers or/and organoclay reinforcement. The incorporation of compatibilizers increases the thermal stability of PP and reduces its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it decreases slightly the Tgs of PP and SAN phases of ABS/PP blends. Regarding the storage modulus of the ABS/PP blends, it presents a change in their behavior at about 10°C and return to their initial behavior at ~110°C. The incorporation of OMMT to no compatibilized and compatibilized ABS/PP blends enhances their storage modulus.

Keywords: acrylonitrile, butadiene, styrene terpolymer, compatibilizer, organoclay, polypropylene

Procedia PDF Downloads 310

Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

Abstract:

At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A³B⁵ and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si_1-xGe_x(x≤0.05) alloys grown by Czochralski technique is studied in initial and ⁶⁰Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: internal friction, shear modulus, gamma-irradiation, SiGe alloys

Procedia PDF Downloads 133

Authors: Gui Yewei, Du Yanxia, Xiao Guangming, Liu Lei, Wei Dong, Yang Xiaofeng

Abstract:

A phase change material (PCM) is a substance which absorbs a large amount of energy when undergoing a change of solid-liquid phase. The good physical and chemical properties of C or SiC foam reveal the possibility of using them as a thermal conductivity enhancer for the PCM. C or SiC foam composite PCM has a high effective conductivity and becomes one of the most interesting thermal storage techniques due to its advantage of simplicity and reliability. The paper developed a numerical method to simulate the heat transfer of SiC and C foam composite PCM, a finite volume technique was used to discretize the heat diffusion equation while the phase change process was modeled using the equivalent specific heat method. The effects of the porosity were investigated based on the numerical method, and the effects of the geometric model of the microstructure on the equivalent thermal conductivity was studies.

Keywords: SiC foam, composite, phase change material, heat transfer

Procedia PDF Downloads 501

Authors: A.Velavan, C. G. Saravanan, M. Vikneswaran, E. James Gunasekaran

Abstract:

In present investigation, experiments were carried out to compare the effect of the ceramic coated piston crown and uncoated piston on combustion, performance and emission characteristics of a port injected Spark Ignited engine. The piston crown was coated with aluminium alloy in the form ceramic oxide layer of thickness 500 µm using micro-arc oxidation technique. This ceramic coating will act as a thermal barrier which reduces in-cylinder heat rejection and increases the durability of the piston by withstanding high temperature and pressure produced during combustion. Flame visualization inside the combustion chamber was carried out using AVL Visioscope combustion analyzer to predict the type of combustion occurs at different load condition. Based on the experimental results, it was found that the coated piston shows an improved thermal efficiency when compared to uncoated piston. This is because more heat presents in the combustion chamber which helps efficient combustion of the fuel. The CO and HC emissions were found to be reduced due to better combustion of the fuel whereas NOx emission was increased due to increase in combustion temperature for ceramic coated piston.

Keywords: coated piston, micro-arc oxidation, thermal barrier, thermal efficiency, visioscope

Procedia PDF Downloads 135

Authors: Prashant S. Humnabad

Abstract:

The objective of this work is to carry out a thermal heat transfer analysis to obtain the time dependent temperature field in welding process friction stir welded dissimilar materials with different preheating temperature. A series of joints were made on four mm thick aluminum and steel plates. The temperature used was 100ºC, 150ºC and 200ºC. The welding operation was performed with different rotational speeds and traverse speed (1000, 1400 and 2000 rmp and 16, 20 and 25 mm/min..). In numerical model, the welded plate was modeled as the weld line is the symmetric line. The work-piece has dimensions of 100x100x4 mm. The obtained result was compared with experimental result, which shows good agreement and within the acceptable limit. The peak temperature at the weld zone increases significantly with respect to increase in process time.

Keywords: FEA, thermal analysis, preheating, friction stir welding

Procedia PDF Downloads 177

Authors: Elsayed M. A. Elbashbeshy, T. G. Emam, M. S. El-Azab, K. M. Abdelgaber

Abstract:

The effect of thermal radiation on flow, heat and mass transfer of an incompressible viscous nanofluid over a stretching horizontal cylinder embedded in a porous medium with suction/injection is discussed numerically. The governing boundary layer equations are reduced to a system of ordinary differential equations. Mathematica has been used to solve such system after obtaining the missed initial conditions. Comparison of obtained numerical results is made with previously published results in some special cases, and found to be in a good agreement.

Keywords: laminar flow, boundary layer, stretching horizontal cylinder, thermal radiation, suction/injection, nanofluid

Procedia PDF Downloads 372

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

Procedia PDF Downloads 140

Authors: Andrey Yatsun, Andrei Malchikov

Abstract:

Exoskeletons are used to support and compensate for the load on the human musculoskeletal system. Elastomers are an important component of exoskeletons, providing additional support and compensating for the load. The algorithm of the active elastomer tension system provides the required auxiliary force depending on the angle of rotation and the tilt speed of the operator's torso. Feedback for the drive is provided by a force sensor integrated into the attachment of the exoskeleton vest. The use of direct force measurement ensures the required accuracy in all settings of the man-machine system. Non-adjustable elastic elements make it difficult to move without load, tilt forward and walk. A strategy for the organization of the auxiliary forces management system is proposed based on the allocation of 4 operating modes of the human-machine system.

Keywords: soft exoskeleton, mathematical modeling, pre-tension elastomer, human-machine interaction

Procedia PDF Downloads 53

Authors: Akhila Konala, Jagadeeswara Reddy Vennapusa, Sujay Chattopadhyay

Abstract:

The energy consumption of humankind is growing day by day due to an increase in the population, industrialization and their needs for living. Fossil fuels are the major source of energy to satisfy energy needs, which are non-renewable energy resources. So, there is a need to develop green resources for energy production and storage. Phase change materials (PCMs) derived from plants (green resources) are well known for their capacity to store the thermal energy as latent heat during their phase change from solid to liquid. This property of PCM could be used for storage of thermal energy. In this study, a composite with fatty acid (caprylic acid; M.P 15°C, Enthalpy 179kJ/kg) as a phase change material and expanded perlite as support porous matrix was prepared through direct impregnation method for thermal energy storage applications. The prepared composite was characterized using Differential scanning calorimetry (DSC), Field Emission Scanning Electron Microscope (FESEM), Thermal Gravimetric Analysis (TGA), and Fourier Transform Infrared (FTIR) spectrometer. The melting point of the prepared composite was 15.65°C, and the melting enthalpy was 82kJ/kg. The surface nature of the perlite was observed through FESEM. It was observed that there are micro size pores in the perlite surface, which were responsible for the absorption of PCM into perlite. In TGA thermogram, the PCM loss from composite was started at ~90°C. FTIR curves proved there was no chemical interaction between the perlite and caprylic acid. So, the PCM composite prepared in this work could be effective to use in temperature maintenance of buildings.

Keywords: caprylic acid, composite, phase change materials, PCM, perlite, thermal energy

Procedia PDF Downloads 111

Authors: Oscar E. Cariceo, Claudia V. Casal

Abstract:

Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

Procedia PDF Downloads 160

Authors: Ochuko K. Overen, Edson L. Meyer

Abstract:

Uncontrolled heat transfer between the inner and outer space of low-cost housings through the thermal envelope result in indoor thermal discomfort. As a result, an excessive amount of energy is consumed for space heating and cooling. Thermo-optical properties are the ability of paints to reduce the rate of heat transfer through the thermal envelope. The aim of this study is to analyze the thermal performance of a low-cost house with its walls inner surface coated with transparent infrared reflective paint. The thermo-optical properties of the paint were analyzed using Scanning Electron Microscopy/ Energy Dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infra-Red (FTIR) and thermal photographic technique. Meteorological indoor and ambient parameters such as; air temperature, relative humidity, solar radiation, wind speed and direction of a low-cost house in Golf-course settlement, South Africa were monitored. The monitoring period covers both winter and summer period before and after coating. The thermal performance of the coated walls was evaluated using time lag and decrement factor. The SEM image shows that the coat is transparent to light. The presence of Al as Al2O and other elements were revealed by the EDX spectrum. Before coating, the average decrement factor of the walls in summer was found to be 0.773 with a corresponding time lag of 1.3 hours. In winter, the average decrement factor and corresponding time lag were 0.467 and 1.6 hours, respectively. After coating, the average decrement factor and corresponding time lag were 0.533 and 2.3 hour, respectively in summer. In winter, an average decrement factor of 1.120 and corresponding time lag of 3 hours was observed. The findings show that the performance of the coats is influenced by the seasons. With a 74% reduction in decrement factor and 1.4 time lag increase in winter, it implies that the coatings have more ability to retain heat within the inner space of the house than preventing heat flow into the house. In conclusion, the results have shown that transparent infrared reflective paint has the ability to reduce the propagation of heat flux through building walls. Hence, it can serve as a remedy to the poor thermal performance of low-cost housings in South Africa.

Keywords: energy efficiency, decrement factor, low-cost housing, paints, rural development, thermal comfort, time lag

Procedia PDF Downloads 274

Authors: Matthew D. Baffa

Abstract:

Infrared thermography is a non-destructive test method used to estimate surface temperatures based on the amount of electromagnetic energy radiated by building envelope components. These surface temperatures are indicators of various qualitative building envelope deficiencies such as locations and extent of heat loss, thermal bridging, damaged or missing thermal insulation, air leakage, and moisture presence in roof, floor, and wall assemblies. Although infrared thermography is commonly used for qualitative deficiency detection in buildings, this study assesses its use as a quantitative method to estimate the overall thermal conductance value (U-value) of the exterior above-grade walls of a study home. The overall U-value of exterior above-grade walls in a home provides useful insight into the energy consumption and thermal comfort of a home. Three methodologies from the literature were employed to estimate the overall U-value by equating conductive heat loss through the exterior above-grade walls to the sum of convective and radiant heat losses of the walls. Outdoor infrared thermography field measurements of the exterior above-grade wall surface and reflective temperatures and emissivity values for various components of the exterior above-grade wall assemblies were carried out during winter months at the study home using a basic thermal imager device. The overall U-values estimated from each methodology from the literature using the recorded field measurements were compared to the nominal exterior above-grade wall overall U-value calculated from materials and dimensions detailed in architectural drawings of the study home. The nominal overall U-value was validated through calendarization and weather normalization of utility bills for the study home as well as various estimated heat loss quantities from a HOT2000 computer model of the study home and other methods. Under ideal environmental conditions, the estimated overall U-values deviated from the nominal overall U-value between ±2% to ±33%. This study suggests infrared thermography can estimate the overall U-value of exterior above-grade walls in low-rise residential homes with a fair amount of accuracy.

Keywords: emissivity, heat loss, infrared thermography, thermal conductance

Procedia PDF Downloads 300

Authors: Kang Zijian, Zhang Tingyu, Burra Venkata Durga Kumar

Abstract:

This article investigates the challenges in memory migration during the live migration of virtual machines. We found three challenges probably existing in pre-copy technology. One of the main challenges is the challenge of downtime migration. Decrease the downtime could promise the normal work for a virtual machine. Although pre-copy technology is greatly decreasing the downtime, we still need to shut down the machine in order to finish the last round of data transfer. This paper provides an optimization scheme for the problems existing in pro-copy technology, mainly the optimization of the dirty page migration mechanism. The typical pre-copy technology copy n-1th’s dirty pages in nth turn. However, our idea is to create a double iteration method to solve this problem.

Keywords: virtual machine, pre-copy technology, memory migration process, downtime, dirty pages migration method

Procedia PDF Downloads 123

Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

Abstract:

Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

Procedia PDF Downloads 48

Authors: P. Halder, A. Zaman

Abstract:

It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 139

Authors: Abhishek Priyam, Prabha Chand

Abstract:

A theoretical investigation on the effect of collector aspect ratio on the thermal performance of wavy finned absorber solar air heaters has been performed. For the constant collector area, the various performance parameters have been calculated for plane and wavy finned solar air heaters. It has been found that the performance of wavy finned solar air heater improved with the increase in the collector aspect ratio. The performance of wavy finned solar air heater has been found 30 percent higher than those of plane solar air heater. The obtained results for wavy fin solar air heaters are compared with the available experimental data of most common type solar air heaters.

Keywords: wavy fin, aspect ratio, solar air heater, thermal efficiency, collector efficiency factor, temperature rise

Procedia PDF Downloads 318

Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

Abstract:

The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

Procedia PDF Downloads 135

Authors: Walid Cherif

Abstract:

Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

Procedia PDF Downloads 456

Authors: Nouredine Benouzza, Ahmed Hamida Boudinar, Azeddine Bendiabdellah

Abstract:

An algorithm for Eccentricity Fault Detection (EFD) applied to a squirrel cage induction machine is proposed in this paper. This algorithm employs the behavior of the stator current spectral analysis and the localization of the Rotor Slot Harmonic (RSH) frequency to detect eccentricity faults in three phase induction machine. The RHS frequency once obtained is used as a key parameter into a simple developed expression to directly compute the eccentricity fault frequencies in the induction machine. Experimental tests performed for both a healthy motor and a faulty motor with different eccentricity fault severities illustrate the effectiveness and merits of the proposed EFD algorithm.

Keywords: squirrel cage motor, diagnosis, eccentricity faults, current spectral analysis, rotor slot harmonic

Procedia PDF Downloads 469

Authors: Rasheed Gbenga Jimoh, Akinbowale Nathaniel Babatunde

Abstract:

The use of Automated Teller Machine (ATM) has become an important tool among commercial banks, customers of banks have come to depend on and trust the ATM conveniently meet their banking needs. Although the overwhelming advantages of ATM cannot be over-emphasized, its alarming fraud rate has become a bottleneck in it’s full adoption in Nigeria. This study examined the menace of ATM in the society another cost of running ATM services by banks in the country. The researcher developed a prototype of an enhanced Automated Teller Machine Authentication using Short Message Service (SMS) Verification. The developed prototype was tested by Ten (10) respondents who are users of ATM cards in the country and the data collected was analyzed using Statistical Package for Social Science (SPSS). Based on the results of the analysis, it is being envisaged that the developed prototype will go a long way in reducing the alarming rate of ATM fraud in Nigeria.

Keywords: ATM, ATM fraud, e-banking, prototyping

Procedia PDF Downloads 300

Authors: Nandy Putra, Atrialdipa Duanovsah, Kristofer Haliansyah

Abstract:

The aim of this research is to design a LHP with low thermal resistance and low condenser temperature. A Self-designed cascade LHP was tested by using biomaterial, sintered copper powder, and aluminum screen mesh as the wick. Using pure water as the working fluid for the first level of the LHP and 96% alcohol as the working fluid for the second level of LHP, the experiments were run with 10W, 20W, and 30W heat input. Experimental result shows that the usage of biomaterial as wick could reduce more temperature at evaporator than by using sintered copper powder and screen mesh up to 22.63% and 37.41% respectively. The lowest thermal resistance occurred during the usage of biomaterial as wick of heat pipe, which is 2.06 ^oC/W. The usage of cascade system could be applied to LHP to reduce the temperature at condenser and reduced thermal resistance up to 17.6%.

Keywords: biomaterial, cascade loop heat pipe, screen mesh, sintered Cu

Procedia PDF Downloads 250