Search results for: strength prediction models.
4042 Effective Class of Discreet Programing Problems
Authors: Kaziyev G. Z., Nabiyeva G. S., Kalizhanova A.U.
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We consider herein a concise view of discreet programming models and methods. There has been conducted the models and methods analysis. On the basis of discreet programming models there has been elaborated and offered a new class of problems, i.e. block-symmetry models and methods of applied tasks statements and solutions.Keywords: Discreet programming, block-symmetry, analysis methods, information systems development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13414041 Comparison of Physical and Chemical Properties of Micro-Silica and Locally Produced Metakaolin and Effect on the Properties of Concrete
Authors: S. U. Khan, T. Ayub, N. Shafiq
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The properties of locally produced metakaolin (MK) as cement replacing material and the comparison of reactivity with commercially available micro-silica have been investigated. Compressive strength, splitting tensile strength, and load-deflection behaviour under bending are the properties that have been studied. The amorphous phase of MK with micro-silica was compared through X-ray diffraction (XRD) pattern. Further, interfacial transition zone of concrete with micro-silica and MK was observed through Field Emission Scanning Electron Microscopy (FESEM). Three mixes of concrete were prepared. One of the mix is without cement replacement as control mix, and the remaining two mixes are 10% cement replacement with micro-silica and MK. It has been found that MK, due to its irregular structure and amorphous phase, has high reactivity with portlandite in concrete. The compressive strength at early age is higher with MK as compared to micro-silica. MK concrete showed higher splitting tensile strength and higher load carrying capacity as compared to control and micro-silica concrete at all ages respectively.
Keywords: Metakaolin, compressive strength, splitting tensile strength, load deflection, interfacial transition zone.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15764040 Using Artificial Neural Network to Predict Collisions on Horizontal Tangents of 3D Two-Lane Highways
Authors: Omer F. Cansiz, Said M. Easa
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The purpose of this study is mainly to predict collision frequency on the horizontal tangents combined with vertical curves using artificial neural network methods. The proposed ANN models are compared with existing regression models. First, the variables that affect collision frequency were investigated. It was found that only the annual average daily traffic, section length, access density, the rate of vertical curvature, smaller curve radius before and after the tangent were statistically significant according to related combinations. Second, three statistical models (negative binomial, zero inflated Poisson and zero inflated negative binomial) were developed using the significant variables for three alignment combinations. Third, ANN models are developed by applying the same variables for each combination. The results clearly show that the ANN models have the lowest mean square error value than those of the statistical models. Similarly, the AIC values of the ANN models are smaller to those of the regression models for all the combinations. Consequently, the ANN models have better statistical performances than statistical models for estimating collision frequency. The ANN models presented in this paper are recommended for evaluating the safety impacts 3D alignment elements on horizontal tangents.Keywords: Collision frequency, horizontal tangent, 3D two-lane highway, negative binomial, zero inflated Poisson, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16284039 Durability Aspects of Recycled Aggregate Concrete: An Experimental Study
Authors: Smitha Yadav, Snehal Pathak
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Aggregate compositions in the construction and demolition (C&D) waste have potential to replace normal aggregates. However, to re-utilise these aggregates, the concrete produced with these recycled aggregates needs to provide the desired compressive strength and durability. This paper examines the performance of recycled aggregate concrete made up of 60% recycled aggregates of 20 mm size in terms of durability tests namely rapid chloride permeability, drying shrinkage, water permeability, modulus of elasticity and creep without compromising the compressive strength. The experimental outcome indicates that recycled aggregate concrete provides strength and durability same as controlled concrete when processed for removal of adhered mortar.
Keywords: Compressive strength, recycled aggregate, shrinkage, rapid chloride permeation test, modulus of elasticity, water permeability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14934038 Metrology-Inspired Methods to Assess the Biases of Artificial Intelligence Systems
Authors: Belkacem Laimouche
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With the field of Artificial Intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.
Keywords: Artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, inter-laboratory comparison, data analysis, data reliability, bias impact assessment, bias measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 944037 Evaluation of Short-Term Load Forecasting Techniques Applied for Smart Micro Grids
Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone
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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.
Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25904036 Evaluating Residual Mechanical and Physical Properties of Concrete at Elevated Temperatures
Authors: S. Hachemi, A. Ounis, S. Chabi
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This paper presents the results of an experimental study on the effects of elevated temperature on compressive and flexural strength of Normal Strength Concrete (NSC), High Strength Concrete (HSC) and High Performance Concrete (HPC). In addition, the specimen mass and volume were measured before and after heating in order to determine the loss of mass and volume during the test. In terms of non-destructive measurement, ultrasonic pulse velocity test was proposed as a promising initial inspection method for fire damaged concrete structure. 100 Cube specimens for three grades of concrete were prepared and heated at a rate of 3°C/min up to different temperatures (150, 250, 400, 600, and 900°C). The results show a loss of compressive and flexural strength for all the concretes heated to temperature exceeding 400°C. The results also revealed that mass and density of the specimen significantly reduced with an increase in temperature.
Keywords: High temperature, Compressive strength, Mass loss, Ultrasonic pulse velocity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22164035 Anisotropic Shear Strength of Sand Containing Plastic Fine Materials
Authors: Alaa H. J. Al-Rkaby, A. Chegenizadeh, H. R. Nikraz
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Anisotropy is one of the major aspects that affect soil behavior, and extensive efforts have investigated its effect on the mechanical properties of soil. However, very little attention has been given to the combined effect of anisotropy and fine contents. Therefore, in this paper, the anisotropic strength of sand containing different fine content (F) of 5%, 10%, 15%, and 20%, was investigated using hollow cylinder tests under different principal stress directions of α = 0° and α = 90°. For a given principal stress direction (α), it was found that increasing fine content resulted in decreasing deviator stress (q). Moreover, results revealed that all fine contents showed anisotropic strength where there is a clear difference between the strength under 0° and the strength under 90°. This anisotropy was greatest under F = 5% while it decreased with increasing fine contents, particularly at F = 10%. Mixtures with low fine content show low contractive behavior and tended to show more dilation. Moreover, all sand-clay mixtures exhibited less dilation and more compression at α = 90° compared with that at α = 0°.Keywords: Anisotropy, principal stress direction, fine content, hollow cylinder sample.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10704034 Churn Prediction: Does Technology Matter?
Authors: John Hadden, Ashutosh Tiwari, Rajkumar Roy, Dymitr Ruta
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The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customer complaints data and provides a comparative analysis of neural networks, regression trees and regression in their capabilities of predicting customer churn.Keywords: Churn, Decision Trees, Neural Networks, Regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32844033 Prediction of Protein Subchloroplast Locations using Random Forests
Authors: Chun-Wei Tung, Chyn Liaw, Shinn-Jang Ho, Shinn-Ying Ho
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Protein subchloroplast locations are correlated with its functions. In contrast to the large amount of available protein sequences, the information of their locations and functions is less known. The experiment works for identification of protein locations and functions are costly and time consuming. The accurate prediction of protein subchloroplast locations can accelerate the study of functions of proteins in chloroplast. This study proposes a Random Forest based method, ChloroRF, to predict protein subchloroplast locations using interpretable physicochemical properties. In addition to high prediction accuracy, the ChloroRF is able to select important physicochemical properties. The important physicochemical properties are also analyzed to provide insights into the underlying mechanism.Keywords: Chloroplast, Physicochemical properties, Proteinlocations, Random Forests.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16634032 Intensity of Singular Stress Field at the Corner of Adhesive Layer in Bonded Plate
Authors: Nao-Aki Noda, Yu Zhang, Ken-Tarou Takaishi, Hiroyuki Shibahara
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In this paper the strength of adhesive joint under tension and bending is discussed on the basis of intensity of singular stress by the application of FEM. A useful method is presented with focusing on the stress at the edge of interface between the adhesive and adherent obtained by FEM. After analyzing the adhesive joint strength with all material combinations, it is found that to improve the interface strength, thin adhesive layers are desirable because the intensity of singular stress decreases with decreasing the thickness.Keywords: Adhesive, Adherent, Intensity of singular stress, Bonded strip
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14954031 Time Series Forecasting Using Various Deep Learning Models
Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan
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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.
Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11194030 Influence Analysis of Macroeconomic Parameters on Real Estate Price Variation in Taipei, Taiwan
Authors: Li Li, Kai-Hsuan Chu
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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.Keywords: Real estate price, least-square, grey correlation, macroeconomics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9724029 Vibration Attenuation Using Functionally Graded Material
Authors: Saeed Asiri, Hassan Hedia, Wael Eissa
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The aim of the work was to attenuate the vibration amplitude in CESNA 172 airplane wing by using Functionally Graded Material instead of uniform or composite material. Wing strength was achieved by means of stress analysis study, while wing vibration amplitudes and shapes were achieved by means of Modal and Harmonic analysis. Results were verified by applying the methodology in a simple cantilever plate to the simple model and the results were promising and the same methodology can be applied to the airplane wing model. Aluminum models, Titanium models, and functionally graded materials of Aluminum and titanium results were compared to show a great vibration attenuation after using the FGM. Optimization in FGM gradation satisfied our objective of reducing and attenuating the vibration amplitudes to show the effect of using FGM in vibration behavior. Testing the Aluminum rich models, and comparing it with the titanium rich model was an optimization in this paper. Results have shown a significant attenuation in vibration magnitudes when using FGM instead of Titanium Plate, and Aluminium wing with FGM Spurs instead of Aluminium wings. It was also recommended that in future, changing the graphical scale to 1:10 or even 1:1 when the computers- capabilities allow.
Keywords: Vibration, Attenuation, FGM, ANSYS2011, FEM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31224028 Optimization of Springback Prediction in U-Channel Process Using Response Surface Methodology
Authors: Muhamad Sani Buang, Shahrul Azam Abdullah, Juri Saedon
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There is not much effective guideline on development of design parameters selection on spring back for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for spring back in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in Uchannel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24 ). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on spring back of flange angle (β2 ) and wall opening angle (β1 ), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the spring back behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for spring back was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values.
Keywords: Advance high strength steel, U-channel process, Springback, Design of Experiment, Optimization, Response Surface Methodology (RSM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22894027 Universities Strategic Evaluation Using Balanced Scorecard
Authors: M. D. Nayeri, M. M. Mashhadi, K. Mohajeri
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Defining strategic position of the organizations within the industry environment is one of the basic and most important phases of strategic planning to which extent that one of the fundamental schools of strategic planning is the strategic positioning school. In today-s knowledge-based economy and dynamic environment, it is essential for universities as the centers of education, knowledge creation and knowledge worker evolvement. Till now, variant models with different approaches to strategic positioning are deployed in defining the strategic position within the various industries. Balanced Scorecard as one of the powerful models for strategic positioning, analyzes all aspects of the organization evenly. In this paper with the consideration of BSC strength in strategic evaluation, it is used for analyzing the environmental position of the best-s Iranian Business Schools. The results could be used in developing strategic plans for these schools as well as other Iranian Management and Business Schools.Keywords: Strategic planning, Strategic position, Balancedscorecard, Higher education institutions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 44254026 The Effects of Plate-Support Condition on Buckling Strength of Rectangular Perforated Plates under Linearly Varying In-Plane Normal Load
Authors: M. Tajdari, A. R. Nezamabadi, M. Naeemi, P. Pirali
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Mechanical buckling analysis of rectangular plates with central circular cutout is performed in this paper. The finiteelement method is used to study the effects of plate-support conditions, aspect ratio, and hole size on the mechanical buckling strength of the perforated plates subjected to linearly varying loading. Results show that increasing the hole size does not necessarily reduce the mechanical buckling strength of the perforated plates. It is also concluded that the clamped boundary condition increases the mechanical buckling strength of the perforated plates more than the simply-supported boundary condition and the free boundary conditions enhance the mechanical buckling strength of the perforated plates more effectively than the fixed boundary conditions. Furthermore, for the bending cases, the critical buckling load of perforated plates with free edges is less than perforated plates with fixed edges.Keywords: Buckling, Perforated plates, Boundary condition, Rectangular plates
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34434025 Zero Inflated Models for Overdispersed Count Data
Authors: Y. N. Phang, E. F. Loh
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The zero inflated models are usually used in modeling count data with excess zeros where the existence of the excess zeros could be structural zeros or zeros which occur by chance. These type of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences which involve sex and health dental epidemiology. The most popular zero inflated models used by many researchers are zero inflated Poisson and zero inflated negative binomial models. In addition, zero inflated generalized Poisson and zero inflated double Poisson models are also discussed and found in some literature. Recently zero inflated inverse trinomial model and zero inflated strict arcsine models are advocated and proven to serve as alternative models in modeling overdispersed count data caused by excessive zeros and unobserved heterogeneity. The purpose of this paper is to review some related literature and provide a variety of examples from different disciplines in the application of zero inflated models. Different model selection methods used in model comparison are discussed.
Keywords: Overdispersed count data, model selection methods, likelihood ratio, AIC, BIC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45144024 Heating and Cooling Scenario of Blended Concrete Subjected to 780 Degrees Celsius
Authors: J. E. Oti, J. M. Kinuthia, R. Robinson, P. Davies
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In this study, the Compressive strength of concretes made with Ground Granulated Blast furnace Slag (GGBS), Pulverised Fuel Ash (PFA), Rice Husk Ash (RHA) and Waste Glass Powder (WGP) after they were exposed 7800C (exposure duration of around 60 minutes) and then allowed to cool down gradually in the furnace for about 280 minutes at water binder ratio of 0.50 was investigated. GGBS, PFA, RHA and WGP were used to replace up to 20% Portland cement in the control concrete. Test for the determination of workability, compressive strength and tensile splitting strength of the concretes were carried out and the results were compared with control concrete. The test results showed that the compressive strength decreased by an average of around 30% after the concretes were exposed to the heating and cooling scenario.
Keywords: Pulverised Fuel Ash, Rice Husk Ash, heating and cooling, concrete.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17754023 Recent Trends in Supply Chain Delivery Models
Authors: Alfred L. Guiffrida
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A review of the literature on supply chain delivery models which use delivery windows to measure delivery performance is presented. The review herein serves to meet the following objectives: (i) provide a synthesis of previously published literature on supply chain delivery performance models, (ii) provide in one paper a consolidation of research that can serve as a single source to keep researchers up to date with the research developments in supply chain delivery models, and (iii) identify gaps in the modeling of supply chain delivery performance which could stimulate new research agendas.
Keywords: Delivery performance, Delivery window, Supply chain delivery models, Supply chain performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23364022 Variability of Soil Strength Parameters and its Effect on the Slope Stability of the Želazny Most Tailing Dam
Authors: Stella A. Arnaouti, Demos C. Angelides, Theodoros N. Chatzigogos, Witold M. Pytel
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The Želazny Most tailing pond is one of the largest facilities worldwide for waste disposal from the copper mines located in South-West Poland. A potential failure of the dam would allow more than 10 million cubic meters of contaminated slurry to flow to the valley, causing immense environmental problems to the surrounding area. Thus, the determination of the strength properties of the dam's soils and their variability is of utmost importance. An extensive site investigation consisting of more than 480 cone penetration tests (CPTs) with or without pore water pressure measurements were conducted within a period of 13 years to study the mechanical properties of the tailings body. The present work investigates the point variability of the soil strength parameters (effective friction angleKeywords: Soil strength variability, friction angle spatial variability, Želazny Most tailing dam.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41624021 The Development of a Low Carbon Cementitious Material Produced from Cement, Ground Granulated Blast Furnace Slag and High Calcium Fly Ash
Authors: Ali Shubbar, Hassnen M. Jafer, Anmar Dulaimi, William Atherton, Ali Al-Rifaie
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This research represents experimental work for investigation of the influence of utilising Ground Granulated Blast Furnace Slag (GGBS) and High Calcium Fly Ash (HCFA) as a partial replacement for Ordinary Portland Cement (OPC) and produce a low carbon cementitious material with comparable compressive strength to OPC. Firstly, GGBS was used as a partial replacement to OPC to produce a binary blended cementitious material (BBCM); the replacements were 0, 10, 15, 20, 25, 30, 35, 40, 45 and 50% by the dry mass of OPC. The optimum BBCM was mixed with HCFA to produce a ternary blended cementitious material (TBCM). The replacements were 0, 10, 15, 20, 25, 30, 35, 40, 45 and 50% by the dry mass of BBCM. The compressive strength at ages of 7 and 28 days was utilised for assessing the performance of the test specimens in comparison to the reference mixture using 100% OPC as a binder. The results showed that the optimum BBCM was the mix produced from 25% GGBS and 75% OPC with compressive strength of 32.2 MPa at the age of 28 days. In addition, the results of the TBCM have shown that the addition of 10, 15, 20 and 25% of HCFA to the optimum BBCM improved the compressive strength by 22.7, 11.3, 5.2 and 2.1% respectively at 28 days. However, the replacement of optimum BBCM with more than 25% HCFA have showed a gradual drop in the compressive strength in comparison to the control mix. TBCM with 25% HCFA was considered to be the optimum as it showed better compressive strength than the control mix and at the same time reduced the amount of cement to 56%. Reducing the cement content to 56% will contribute to decrease the cost of construction materials, provide better compressive strength and also reduce the CO2 emissions into the atmosphere.
Keywords: Cementitious material, compressive strength, GGBS, HCFA, OPC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9904020 Effect of Concrete Nonlinear Parameters on the Seismic Response of Concrete Gravity Dams
Authors: Z. Heirany, M. Ghaemian
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Behavior of dams against the seismic loads has been studied by many researchers. Most of them proposed new numerical methods to investigate the dam safety. In this paper, to study the effect of nonlinear parameters of concrete in gravity dams, a twodimensional approach was used including the finite element method, staggered method and smeared crack approach. Effective parameters in the models are physical properties of concrete such as modulus of elasticity, tensile strength and specific fracture energy. Two different models were used in foundation (mass-less and massed) in order to determine the seismic response of concrete gravity dams. Results show that when the nonlinear analysis includes the dam- foundation interaction, the foundation-s mass, flexibility and radiation damping are important in gravity dam-s response.Keywords: Numerical methods; concrete gravity dams; finiteelement method; boundary condition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23254019 Degradability Studies of Photodegradable Plastic Film
Authors: Nurul, A.M.Y., Rahmah, M., Muhammad, A.
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Polypropylene blended with natural oil and pigment additives has been studied. Different formulations for each compound were made into polybag used for cultivation of oil palm seedlings for strength and mechanical properties studies. One group of sample was exposed under normal sunlight to initiate degradation and another group of sample was placed under shaded area for five months. All samples were tested for tensile strength to determine the degradation effects. The tensile strength of directly exposed sunlight samples and shaded area showed up to 50% and 25% degradation respectively. However, similar reduction of Young’s modulus for all samples was found for both exposures. Structural investigations were done using FTIR to detect deformation. The natural additives that were used in the studies were all natural and environmental friendly
Keywords: Agriculture, mechanical strength, photodegradable polymer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27404018 Surface Modification of Titanium Alloy with Laser Treatment
Authors: Nassier A. Nassir, Robert Birch, D. Rico Sierra, S. P. Edwardson, G. Dearden, Zhongwei Guan
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The effect of laser surface treatment parameters on the residual strength of titanium alloy has been investigated. The influence of the laser surface treatment on the bonding strength between the titanium and poly-ether-ketone-ketone (PEKK) surfaces was also evaluated and compared to those offered by titanium foils without surface treatment to optimize the laser parameters. Material characterization using an optical microscope was carried out to study the microstructure and to measure the mean roughness value of the titanium surface. The results showed that the surface roughness shows a significant dependency on the laser power parameters in which surface roughness increases with the laser power increment. Moreover, the results of the tensile tests have shown that there is no significant dropping in tensile strength for the treated samples comparing to the virgin ones. In order to optimize the laser parameter as well as the corresponding surface roughness, single-lap shear tests were conducted on pairs of the laser treated titanium stripes. The results showed that the bonding shear strength between titanium alloy and PEKK film increased with the surface roughness increment to a specific limit. After this point, it is interesting to note that there was no significant effect for the laser parameter on the bonding strength. This evidence suggests that it is not necessary to use very high power of laser to treat titanium surface to achieve a good bonding strength between titanium alloy and the PEKK film.
Keywords: Bonding strength, laser surface treatment, PEKK, titanium alloy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8464017 Pre-Operative Tool for Facial-Post-Surgical Estimation and Detection
Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary
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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.
Keywords: K-nearest neighbor, face detection, vitiligo, bone deformity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6874016 Forecasting Foreign Direct Investment with Modified Diffusion Model
Authors: Bi-Huei Tsai
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Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected data for the best accuracy. Particularly, Taiwanese regulatory FDI restrictions are also considered in our modified model to meet the realistic conditions. To validate the model-s effectiveness, this investigation compares the prediction accuracy of modified model with the conventional diffusion model, which does not take account of the profitability factors. The results clearly demonstrate the internal influence to be positive, as early FDI adopters- consistent praises of FDI attract potential firms to make the same move. The former erects a behavior model for the latter to imitate their foreign investment decision. Particularly, the results of modified diffusion models show that the earnings from Chinese branches are positively related to the internal influence. In general, the imitating tendency of potential consumers is substantially hindered by the losses in the Chinese branches, and these firms would invest less into China. The FDI inflow extension depends on earnings of Chinese branches, and companies will adjust their FDI strategies based on the returns. Since this research has proved that earning is an influential factor on FDI dynamics, our revised model explicitly performs superior in prediction ability than conventional diffusion model.Keywords: diffusion model, genetic algorithms, nonlinear leastsquares (NLS) model, prediction error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16044015 Power MOSFET Models Including Quasi-Saturation Effect
Authors: Abdelghafour Galadi
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In this paper, accurate power MOSFET models including quasi-saturation effect are presented. These models have no internal node voltages determined by the circuit simulator and use one JFET or one depletion mode MOSFET transistors controlled by an “effective” gate voltage taking into account the quasi-saturation effect. The proposed models achieve accurate simulation results with an average error percentage less than 9%, which is an improvement of 21 percentage points compared to the commonly used standard power MOSFET model. In addition, the models can be integrated in any available commercial circuit simulators by using their analytical equations. A description of the models will be provided along with the parameter extraction procedure.
Keywords: Power MOSFET, drift layer, quasi-saturation effect, SPICE model, circuit simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20114014 The Reliability of the Improved e-N Method for Transition Prediction as Checked by PSE Method
Authors: Caihong Su
Abstract:
Transition prediction of boundary layers has always been an important problem in fluid mechanics both theoretically and practically, yet notwithstanding the great effort made by many investigators, there is no satisfactory answer to this problem. The most popular method available is so-called e-N method which is heavily dependent on experiments and experience. The author has proposed improvements to the e-N method, so to reduce its dependence on experiments and experience to a certain extent. One of the key assumptions is that transition would occur whenever the velocity amplitude of disturbance reaches 1-2% of the free stream velocity. However, the reliability of this assumption needs to be verified. In this paper, transition prediction on a flat plate is investigated by using both the improved e-N method and the parabolized stability equations (PSE) methods. The results show that the transition locations predicted by both methods agree reasonably well with each other, under the above assumption. For the supersonic case, the critical velocity amplitude in the improved e-N method should be taken as 0.013, whereas in the subsonic case, it should be 0.018, both are within the range 1-2%.Keywords: Boundary layer, e-N method, PSE, Transition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14984013 A Proposed Performance Prediction Approach for Manufacturing Processes using ANNs
Authors: M. S. Abdelwahed, M. A. El-Baz, T. T. El-Midany
Abstract:
this paper aims to provide an approach to predict the performance of the product produced after multi-stages of manufacturing processes, as well as the assembly. Such approach aims to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. The approach is guided by a six-sigma methodology to obtain improved performance. In this paper a case study of the manufacture of a hermetic reciprocating compressor is presented. The application of artificial neural networks (ANNs) technique is introduced to improve performance prediction within this manufacturing environment. The results demonstrate that the approach predicts accurately and effectively.Keywords: Artificial neural networks, Reciprocating compressor manufacturing, Performance prediction, Quality improvement
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