Search results for: transient temperature prediction

Authors: Shree Laxmi Prashant, Subhash C. Yaragal, K. S. Babu Narayan

Abstract:

Concrete is found to undergo degradation when subjected to elevated temperatures and loose substantial amount of its strength. The loss of strength in concrete is mainly attributed to decomposition of C-S-H and release of physically and chemically bound water, which begins when the exposure temperature exceeds 100°C. When such a concrete comes in contact with moisture, the cement paste is found rehydrate and considerable amount of strength lost is found to recover. This paper presents results of an experimental program carried out to investigate the effect of recuring on strength gain of OPC concrete specimens subjected to elevated temperatures from 200°C to 800°C, which were subjected to retention time of two hours and four hours at the designated temperature. Strength recoveries for concrete subjected to 7 designated elevated temperatures are compared. It is found that the efficacy of recuring as a measure of strength recovery reduces with increase in exposure temperature.

Keywords: Elevated Temperature, Recuring, Strength Recovery, Compressive strength.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2442

Authors: Suzan Wedyan

Abstract:

Associative classification (AC) is a data mining approach that combines association rule and classification to build classification models (classifiers). AC has attracted a significant attention from several researchers mainly because it derives accurate classifiers that contain simple yet effective rules. In the last decade, a number of associative classification algorithms have been proposed such as Classification based Association (CBA), Classification based on Multiple Association Rules (CMAR), Class based Associative Classification (CACA), and Classification based on Predicted Association Rule (CPAR). This paper surveys major AC algorithms and compares the steps and methods performed in each algorithm including: rule learning, rule sorting, rule pruning, classifier building, and class prediction.

Keywords: Associative Classification, Classification, Data Mining, Learning, Rule Ranking, Rule Pruning, Prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6633

Authors: Mário C. Ricci

Abstract:

A new, rapidly convergent, numerical procedure for internal loading distribution computation in statically loaded, singlerow, angular-contact ball bearings, subjected to a known combined radial and thrust load, which must be applied so that to avoid tilting between inner and outer rings, is used to find the load distribution differences between a loaded unfitted bearing at room temperature, and the same loaded bearing with interference fits that might experience radial temperature gradients between inner and outer rings. For each step of the procedure it is required the iterative solution of Z + 2 simultaneous nonlinear equations – where Z is the number of the balls – to yield exact solution for axial and radial deflections, and contact angles.

Keywords: Ball, Bearing, Static, Load, Iterative, Numerical, Method, Temperature, Fit.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1786

Authors: U. Narumitbowonkul, P. Keangin, P. Rattanadecho

Abstract:

The characteristics of temperature distribution and electric field in a natural rubber glove (NRG) using microwave energy during microwave heating process are investigated numerically and experimentally. A three-dimensional model of NRG and microwave oven are considered in this work. The influences of position, heating time and rotation angle of NRG on temperature distribution and electric field are presented in details. The coupled equations of electromagnetic wave propagation and heat transfer are solved using the finite element method (FEM). The numerical model is validated with an experimental study at a frequency of 2.45 GHz. The results show that the numerical results closely match the experimental results. Furthermore, it is found that the temperature distribution and electric field increases with increasing heating time. The hot spot zone appears in NRG at the tip of middle finger while the maximum temperature occurs in case of rotation angle of NRG = 60 degree. This investigation provides the essential aspects for a fundamental understanding of heat transport of NRG using microwave energy in industry.

Keywords: Electric field, Finite element method, Microwave energy, Natural rubber glove.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2191

Authors: Sandra Ghavam Shirazi, Komeil Valipourian, Mohammad Reza Golhashem

Abstract:

This paper represents the basic idea and mechanisms associated with the durability of geomembranes and discusses the factors influencing the service life and temperature of geomembrane liners. Geomembrane durability is stated as field performance and laboratory test outcomes under various conditions. Due to the high demand of geomembranes as landfill barriers and their crucial role in sensitive projects, sufficient service life of geomembranes is very important, therefore in this paper, the durability, the effect of temperature on geomembrane and the role of this type of reinforcement in different types of soil will be discussed. Also, the role of geomembrane in the earthquake will be considered in the last part of the paper.

Keywords: Geomembrane, durability temperature soil mechanic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 932

Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

Abstract:

Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.

Keywords: Interaction graph, Negative training data, Protein-Protein interaction, Support vector machine.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1702

Authors: Sreeyuth Lal, Yohei Sato, Bojan Niceno

Abstract:

With the long-term objective of Critical Heat Flux (CHF) prediction, a Direct Numerical Simulation (DNS) framework for simulation of subcooled and saturated nucleate pool boiling is developed. One case of saturated, and three cases of subcooled boiling at different subcooling levels are simulated. Grid refinement study is also reported. Both boiling and condensation phenomena can be computed simultaneously in the proposed numerical framework. Computed bubble detachment diameters of the saturated nucleate pool boiling cases agree well with the experiment. The flow structures around the growing bubble are presented and the accompanying physics is described. The relation between heat flux evolution from the heated wall and the bubble growth is studied, along with investigations of temperature distribution and flow field evolutions.

Keywords: CFD, interface tracking method, phase change model, subcooled nucleate pool boiling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2464

Authors: W. Afef, A. Mohamed Ammar, G. Kamel, O. Ahmed

Abstract:

In the present study, a numerical approach to describe the pyrolysis of a single solid particle of wood is used to study the influence of various conditions such as particle size, heat transfer coefficient, reactor temperature and heating rate. The influence of these parameters in the change of the duration of the pyrolysis cycle was studied. Mathematical modeling was employed to simulate the heat, mass transfer, and kinetic processes inside the reactor. The evolutions of the mass loss as well as the evolution of temperature inside the thick piece are investigated numerically. The elaborated model was also employed to study the effect of the reactor temperature and the rate of heating on the change of the temperature and the local loss of the mass inside the piece of wood. The obtained results are in good agreement with the experimental data available in the literature.

Keywords: Wood, Pyrolysis, Modeling, Convective heat transfer, Kinetic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1374

Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

Abstract:

In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: Thermal remote sensing, insolation model, land surface temperature, geothermal anomalies.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1025

Authors: N. Zanganeh, M. Zabet

Abstract:

Lactulose is a synthetic disaccharide which has remarkable applications in food and pharmaceutical fields. Lactulose is not found in nature and it is produced by isomerization reaction of lactose in an alkaline environment. It should be noted that this reaction has a very low yield since significant amount of lactose stays un-reacted in the system. Basically, purification of lactulose is difficult and costly. Previous studies have revealed that solubility of lactose and lactulose are significantly different in ethanol. Considering the fact that solubility is also affected by temperature itself, we investigated the effect of ethanol and temperature on separation process of lactose from the syrup containing lactose and lactulose. For this purpose, a saturated solution containing lactulose and lactose was made at three different temperatures; 25⁰C (room temperature), 31⁰C, and 37⁰C first.  Five samples containing 2g saturated solution was taken and then 2g, 3g, 4g, 5g, and 6g ethanol separately was added to the sampling tubes. Sampling tubes were kept at respective temperatures afterward. The concentration of lactose and lactulose after separation process measured and analyzed by High Performance Liquid Chromatography (HPLC). Results showed that ethanol has such a greater impact than operating temperature on purification process. Also, it was observed that the maximum rate of separation occurred at initial amount of added ethanol.

Keywords: Ethanol, lactose, lactulose syrup, purification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1121

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: Factorization machines, feature engineering, negative ratings, recommendation systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 941

Authors: Mohammed T. Hayajneh

Abstract:

Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: Composite, fuzzy, tool life, wear.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2088

Authors: Thanapiyawanit Bancha, Lu Jau-Huai

Abstract:

In this study, we developed a model to predict the temperature and the pressure variation in an internal combustion engine operated in HCCI (Homogeneous charge compression ignition) mode. HCCI operation begins from aspirating of homogeneous charge mixture through intake valve like SI (Spark ignition) engine and the premixed charge is compressed until temperature and pressure of mixture reach autoignition point like diesel engine. Combustion phase was described by double-Wiebe function. The single zone model coupled with an double-Wiebe function were performed to simulated pressure and temperature between the period of IVC (Inlet valve close) and EVO (Exhaust valve open). Mixture gas properties were implemented using STANJAN and transfer the results to main model. The model has considered the engine geometry and enables varying in fuelling, equivalence ratio, manifold temperature and pressure. The results were compared with the experiment and showed good correlation with respect to combustion phasing, pressure rise, peak pressure and temperature. This model could be adapted and use to control start of combustion for HCCI engine.

Keywords: Double-Wiebe function, HCCI, Ignition enhancer, Single zone model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2802

Authors: Hossein Morshedlou, Ahmad Abdollahzade Barforoush

Abstract:

Recent developments in storage technology and networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data streams.

Keywords: Data Stream, Classification, Concept Shift, History.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1278

Authors: Hikaru Sato, Hiroatsu Fukuda, Yupeng Wang

Abstract:

The aim of this study is to analyze influence of differences of heat insulation methods on indoor thermal environment and comfort of apartment buildings. This study analyzes indoor thermal environment and comfort on units of apartment buildings using calculation software "THERB" and compares three different kinds of heat insulation methods. Those are outside insulation on outside walls, inside insulation on outside walls and interior insulation. In terms of indoor thermal environment, outside insulation is the best to stabilize room temperature. In winter, room temperature on outside insulation after heating is higher than other and it is kept 3-5 degrees higher through all night. But the surface temperature with outside insulation did not dramatically increase when heating was used, which was 3 to 5oC lower than the temperature with other insulation. The PMV of interior insulation fall nearly range of comfort when the heating and cooling was use.

Keywords: Apartment Building, Indoor Thermal Environment, Insulation, PMV

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1360

Authors: J. McCullagh, T. Whitfort

Abstract:

Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.

Keywords: Artificial Neural Networks, data, injuries, sport

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2889

Authors: M. Bohlouli, M. Analoui

Abstract:

For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.

Keywords: Active Database, Grid Computing, ResourceRequirement Prediction, Scheduling,

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432

Authors: N.Poolsawad, C.Kambhampati, J. G. F. Cleland

Abstract:

In this paper, we investigated the characteristic of a clinical dataseton the feature selection and classification measurements which deal with missing values problem.And also posed the appropriated techniques to achieve the aim of the activity; in this research aims to find features that have high effect to mortality and mortality time frame. We quantify the complexity of a clinical dataset. According to the complexity of the dataset, we proposed the data mining processto cope their complexity; missing values, high dimensionality, and the prediction problem by using the methods of missing value replacement, feature selection, and classification.The experimental results will extend to develop the prediction model for cardiology.

Keywords: feature selection, missing values, classification, clinical dataset, heart failure.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3211

Authors: Liangliang Tang, Chang Xu, Xingying Chen

Abstract:

GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.

Keywords: Thermophotovoltaic cell, GaSb, GaInAsSb, diffused emitters.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1174

Authors: M. Anwar, M. G. Rasul, M. M. K. Khan

Abstract:

The benefits of rooftop greenery systems (such as energy savings, reduction of greenhouse gas emission for mitigating climate change and maintaining sustainable development, indoor temperature control etc.) in buildings are well recognized, however there remains very little research conducted for quantifying the benefits in subtropical climates such as in Australia. This study mainly focuses on measuring/determining temperature profile and air conditioning energy savings by implementing rooftop greenery systems in subtropical Central Queensland in Australia. An experimental set-up was installed at Rockhampton campus of Central Queensland University, where two standard shipping containers (6m x 2.4m x 2.4m) were converted into small offices, one with green roof and one without. These were used for temperature, humidity and energy consumption data collection. The study found that an energy savings of up to 11.70% and temperature difference of up to 4°C can be achieved in March in subtropical Central Queensland climate in Australia. It is expected that more energy can be saved in peak summer days (December/February) as temperature difference between green roof and non-green roof is higher in December- February.

Keywords: Extensive green roof, Rooftop greenery system, Subtropical climate, Shipping container.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2045

Authors: Jung-in Yoon, Seung-taek Oh, Seung-moon Baek, Jun-hyuk Choi, Jong-yeong Byun, Seok-kwon Jeong, Choon-guen Moon

Abstract:

In this study, we experiment on precise control outlet temperature of water from the water cooler with hot-gas bypass method based on PI control logic for machine tool. Recently, technical trend for machine tools is focused on enhancement of speed and accuracy. High speedy processing causes thermal and structural deformation of objects from the machine tools. Water cooler has to be applied to machine tools to reduce the thermal negative influence with accurate temperature controlling system. The goal of this study is to minimize temperature error in steady state. In addition, control period of an electronic expansion valve were considered to increment of lifetime of the machine tools and quality of product with a water cooler.

Keywords: Hot-gas bypass, Water cooler, PI control, Electronic Expansion Valve, Gain tuning

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3160

Authors: M.kayhani, M.Nourouzi, A. Amiri Delooei

Abstract:

This study presents an exact general solution for steady-state conductive heat transfer in cylindrical composite laminates. Appropriate Fourier transformation has been obtained using Sturm-Liouville theorem. Series coefficients are achieved by solving a set of equations that related to thermal boundary conditions at inner and outer of the cylinder, also related to temperature continuity and heat flux continuity between each layer. The solution of this set of equations are obtained using Thomas algorithm. In this paper, the effect of fibers- angle on temperature distribution of composite laminate is investigated under general boundary conditions. Here, we show that the temperature distribution for any composite laminates is between temperature distribution for laminates with θ = 0° and θ = 90° .

Keywords: exact solution, composite laminate, heat conduction, cylinder, Fourier transformation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2447

Authors: Eakkasak Susakunphaisan, Pichai Namprakai, Withaya Puangsombut

Abstract:

The objective of this paper was to designing a ventilation system to enhance the performance of roof solar collector (RSC) for reducing heat accumulation inside the house. The RSC has 1.8 m2 surface area made of CPAC monier roof tiles on the upper part and gypsum board on the lower part. The space between CPAC monier and gypsum board was fixed at 14 cm. Ventilation system of modified roof solar collector (modified RSC) consists of 9 tubes of 0.15m diameter and installed in the lower part of RSC. Experimental result showed that the temperature of the room, and attic temperature. The average temperature reduction of room of house used modified RSC is about 2oC. and the percentage of room temperature reduction varied between 0 to 10%. Therefore, modified RSC is an interesting option in the sense that it promotes solar energy and conserve energy.

Keywords: roof solar collector, heat accumulation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1512

Authors: Chia-Ling Chang, Chung-Sheng Liao

Abstract:

The present study focuses on the discussion over the parameter of Artificial Neural Network (ANN). Sensitivity analysis is applied to assess the effect of the parameters of ANN on the prediction of turbidity of raw water in the water treatment plant. The result shows that transfer function of hidden layer is a critical parameter of ANN. When the transfer function changes, the reliability of prediction of water turbidity is greatly different. Moreover, the estimated water turbidity is less sensitive to training times and learning velocity than the number of neurons in the hidden layer. Therefore, it is important to select an appropriate transfer function and suitable number of neurons in the hidden layer in the process of parameter training and validation.

Keywords: Artificial Neural Network (ANN), sensitivity analysis, turbidity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2813

Authors: Xi Yang, Bulent Chavdar, Alan Vonseggern, Taylan Altan

Abstract:

Fracture in hot precision forging of engine valves was investigated in this paper. The entire valve forging procedure was described and the possible cause of the fracture was proposed. Finite Element simulation was conducted for the forging process, with commercial Finite Element code DEFORMTM. The effects of material properties, the effect of strain rate and temperature were considered in the FE simulation. Two fracture criteria were discussed and compared, based on the accuracy and reliability of the FE simulation results. The selected criterion predicted the fracture location and shows the trend of damage increasing with good accuracy, which matches the experimental observation. Additional modification of the punch shapes was proposed to further reduce the tendency of fracture in forging. Finite Element comparison shows a great potential of such application in the mass production.

Keywords: Hot forging, engine valve, fracture, tooling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2862

Authors: J. K. Alhassan, B. Attah, S. Misra

Abstract:

Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2417

Authors: Radha Krishan, Deepak Khare, Bhaskar R. Nikam, Ayush Chandrakar

Abstract:

Every irrigation project is planned considering long-term historical climatic conditions; however, the prompt climatic shift and change has come out with such circumstances which were inconceivable in the past. Considering this fact, scrutiny of rainfall and temperature trend has been carried out over the command area of Eastern Ganga Canal project for pre-climate shift period and post-climate shift periods in the present study. Non-parametric Mann-Kendall and Sen’s methods have been applied to study the trends in annual rainfall, seasonal rainfall, annual rainy day, monsoonal rainy days, average annual temperature and seasonal temperature. The results showed decreasing trend of 48.11 to 42.17 mm/decade in annual rainfall and 79.78 tSo 49.67 mm/decade in monsoon rainfall in pre-climate to post-climate shift periods, respectively. The decreasing trend of 1 to 4 days/decade has been observed in annual rainy days from pre-climate to post-climate shift period. Trends in temperature revealed that there were significant decreasing trends in annual (-0.03 ºC/yr), Kharif (-0.02 ºC/yr), Rabi (-0.04 ºC/yr) and summer (-0.02 ºC/yr) season temperature during pre-climate shift period, whereas the significant increasing trend (0.02 ºC/yr) has been observed in all the four parameters during post climate shift period. These results will help project managers in understanding the climate shift and lead them to develop alternative water management strategies.

Keywords: Climate shift, Rainfall trend, temperature trend, Mann-Kendall test, Sen slope estimator, Eastern Ganga Canal command.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 717

Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

Abstract:

Understanding the causes of a road accident and predicting their occurrence is key to prevent deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network. 

Keywords: Accident risks estimation, artificial neural network, deep learning, K-mean, road safety.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 974

Authors: Wardah, T., Kamil, A.A., Sahol Hamid, A.B., Maisarah, W.W.I

Abstract:

Quantitative precipitation forecast (QPF) from atmospheric model as input to hydrological model in an integrated hydro-meteorological flood forecasting system has been operational in many countries worldwide. High-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km have great potential in contributing towards reasonably accurate QPF. In this study the potential of two NWP models to forecast precipitation for a flood-prone area in a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models are statistically verified with the observed rain in Kelantan River Basin, Malaysia. The statistical verification indicates that the models have performed quite satisfactorily for low and moderate rainfall but not very satisfactory for heavy rainfall.

Keywords: MM5, Numerical weather prediction (NWP), quantitative precipitation forecast (QPF), WRF

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2930

Authors: D. Gazdič, I. Hájková, M. Fridrichová

Abstract:

This paper involved the performance of a hightemperature X-Ray powder diffraction analysis (XRD) of a sample of chemical gypsum generated in the production of titanium white; this gypsum originates by neutralizing highly acidic water with limestone suspension. Specifically, it was gypsum formed in the first stage of neutralization when the resulting material contains, apart from gypsum, a number of waste products resulting from the decomposition of ilmenite by sulphuric acid. So it can be described as red titanogypsum. By conducting the experiment using XRD apparatus Bruker D8 Advance with a Cu anode (λkα=1.54184 Å) equipped with high-temperature chamber Anton Paar HTK 16, it was possible to identify clearly in the sample each phase transition in the system of CaSO4·xH2O.

Keywords: Anhydrite, Gypsum, Bassanite, Hematite, XRD, Powder, High-Temperature.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2089