Search results for: material models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12654

Search results for: material models

11244 The Model Establishment and Analysis of TRACE/FRAPTRAN for Chinshan Nuclear Power Plant Spent Fuel Pool

Authors: J. R. Wang, H. T. Lin, Y. S. Tseng, W. Y. Li, H. C. Chen, S. W. Chen, C. Shih

Abstract:

TRACE is developed by U.S. NRC for the nuclear power plants (NPPs) safety analysis. We focus on the establishment and application of TRACE/FRAPTRAN/SNAP models for Chinshan NPP (BWR/4) spent fuel pool in this research. The geometry is 12.17 m × 7.87 m × 11.61 m for the spent fuel pool. In this study, there are three TRACE/SNAP models: one-channel, two-channel, and multi-channel TRACE/SNAP model. Additionally, the cooling system failure of the spent fuel pool was simulated and analyzed by using the above models. According to the analysis results, the peak cladding temperature response was more accurate in the multi-channel TRACE/SNAP model. The results depicted that the uncovered of the fuels occurred at 2.7 day after the cooling system failed. In order to estimate the detailed fuel rods performance, FRAPTRAN code was used in this research. According to the results of FRAPTRAN, the highest cladding temperature located on the node 21 of the fuel rod (the highest node at node 23) and the cladding burst roughly after 3.7 day.

Keywords: TRACE, FRAPTRAN, BWR, spent fuel pool

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11243 Analytical Description of Disordered Structures in Continuum Models of Pattern Formation

Authors: Gyula I. Tóth, Shaho Abdalla

Abstract:

Even though numerical simulations indeed have a significant precursory/supportive role in exploring the disordered phase displaying no long-range order in pattern formation models, studying the stability properties of this phase and determining the order of the ordered-disordered phase transition in these models necessitate an analytical description of the disordered phase. First, we will present the results of a comprehensive statistical analysis of a large number (1,000-10,000) of numerical simulations in the Swift-Hohenberg model, where the bulk disordered (or amorphous) phase is stable. We will show that the average free energy density (over configurations) converges, while the variance of the energy density vanishes with increasing system size in numerical simulations, which suggest that the disordered phase is a thermodynamic phase (i.e., its properties are independent of the configuration in the macroscopic limit). Furthermore, the structural analysis of this phase in the Fourier space suggests that the phase can be modeled by a colored isotropic Gaussian noise, where any instant of the noise describes a possible configuration. Based on these results, we developed the general mathematical framework of finding a pool of solutions to partial differential equations in the sense of continuous probability measure, which we will present briefly. Applying the general idea to the Swift-Hohenberg model we show, that the amorphous phase can be found, and its properties can be determined analytically. As the general mathematical framework is not restricted to continuum theories, we hope that the proposed methodology will open a new chapter in studying disordered phases.

Keywords: fundamental theory, mathematical physics, continuum models, analytical description

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11242 A Review on the Outlook of the Circular Economy in the Automotive Industry

Authors: A. Buruzs, A. Torma

Abstract:

The relationship of the automotive industry with raw material supply is a major challenge and presents obstacles. Automobiles are ones of the most complex products using a large variety of materials. Safety, eco-friendliness and comfort requirements, physical, chemical and economic limitations set the framework in which this industry continuously optimizes the efficient and responsible use of resources. The concept of circular economy covers the issues of waste generation, resource scarcity and economic advantages. However, circularity is already known for the automobile industry – several efforts are done to foster material reuse, product remanufacturing and recycling. The aim of this study is to give an overview on how the producers comply with the growing demands on one hand, and gain efficiency and increase profitability on the other hand from circular economy.

Keywords: automotive industry, circular economy, international requirements, natural resources

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11241 Characterization of Porosity and Flow in Solid Oxide Fuel Cell with 3D Focused Ion Beam Serial Slicing

Authors: Daniel Phifer, Anna Prokhodtseva

Abstract:

DualBeam (FIB-SEM) has long been the technology of choice to sub-sample and characterize materials at site-specific locations which are difficult or impossible to extract by conventional embedding/polishing methods. Whereas Ga based FIB provides excellent resolution and enables precise material removal, the current is usually limited and only allows the extraction of small material biopsies typically ranging from 5-70um wide. Xe Plasma FIB, by contrast, has around 38x more current and can remove more material at the same time to extract significant sized chunks (100-1000um) of materials for further analysis. This increased volume has enabled time-prohibitive investigations like large grain 3D serial sectioning and EBSD and micro-machining for micro-mechanical testing. Investigation of the pore spaces with 3D modeling can determine the relative characteristics of the materials to help design or select properties for best function. Pore spaces can be described with a tortuosity number which is calculated by modules in the 3D analysis software. Xe Plasma FIB technology provides a workflow with sufficient volume to characterize porosity when both large-volume 3D materials characterization and nanometer resolution is required to understand the system.

Keywords: dual-beam, FIB-SEM, porosity, SOFC, solid oxide fuel cell

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11240 Ionic Liquids as Corrosion Inhibitors in CO2 Capture Systems

Authors: A. Acidi, A. Abbaci

Abstract:

We present the viability of using thermally stable, practically non-volatile ionic liquids as corrosion inhibitors in aqueous monoethanolamine system. Carbon steel 1020, which widely used as construction material in CO2 capture plants, has been taken as a test material. Corrosion inhibition capacities of typical room-temperature ionic liquids constituting imidazolium cation in concentration range ≤ 3% by weight in CO2 capture applications were investigated. Electrochemical corrosion experiments using the potentiodynamic polarization technique for measuring corrosion current were carried out. The results show that ionic liquids possess ability to suppressing severe operational problems of corrosion in typical CO2 capture plants.

Keywords: carbon dioxide, carbon steel, monoethanolamine, corrosion rate, ionic liquids, tafel fit

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11239 Transitivity Analysis in Reading Passage of English Text Book for Senior High School

Authors: Elitaria Bestri Agustina Siregar, Boni Fasius Siregar

Abstract:

The paper concerned with the transitivity in the reading passage of English textbook for Senior High School. The six types of process were occurred in the passages with percentage as follows: Material Process is 166 (42%), Relational Process is 155 (39%), Mental Process is 39 (10%), Verbal Process is 21 (5%), Existential Process is 13 (3), and Behavioral Process is 5 (1%). The material processes were found to be the most frequently used process type in the samples in our corpus (41,60 %). This indicates that the twenty reading passages are centrally concerned with action and events. Related to developmental psychology theory, this book fits the needs of students of this age.

Keywords: transitivity, types of processes, reading passages, developmental psycholoy

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11238 Numerical Investigation of the Jacketing Method of Reinforced Concrete Column

Authors: S. Boukais, A. Nekmouche, N. Khelil, A. Kezmane

Abstract:

The first intent of this study is to develop a finite element model that can predict correctly the behavior of the reinforced concrete column. Second aim is to use the finite element model to investigate and evaluate the effect of the strengthening method by jacketing of the reinforced concrete column, by considering different interface contact between the old and the new concrete. Four models were evaluated, one by considering perfect contact, the other three models by using friction coefficient of 0.1, 0.3 and 0.5. The simulation was carried out by using Abaqus software. The obtained results show that the jacketing reinforcement led to significant increase of the global performance of the behavior of the simulated reinforced concrete column.

Keywords: strengthening, jacketing, rienforced concrete column, Abaqus, simulation

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11237 The Way of the English Use of Businessmen for the ASEAN Economic Community in Chonburi Province

Authors: Kittivate Boonyopakorn

Abstract:

The purposes of this study were to investigate the method of the English use of the businessmen and to study their behavior of the utilization for the ASEAN economic community. The participants were divided into the three types of the merchants including the construction contractors, the construction material traders, and SME entrepreneurs. Survey questionnaires and interviews were used in this study. The findings showed that in the type of traders, 23 of the participants are construction contractors, 121 are construction material traders, and 206 are SME entrepreneurs. The study of English in language institute is highly 51.4%. The use of Google in translating English into Thai is 41.7%. Learning English themselves is 41.1% respectively. The businessmen study English for readiness for their trade.

Keywords: way of rnglish use, businessmen, ASEAN economic community, Chonburi province

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11236 Use of Industrial Wastes for Production of Low-Cost Building Material

Authors: Frank Aneke, Elizabeth Theron

Abstract:

Demand for building materials in the last decade due to growing population, has caused scarcity of low-cost housing in South Africa. The investigation thoroughly examined dolomitic waste (DW), silica fume (SF) and River sand (RS) effects on the geotechnical behaviour of fly ash bricks. Bricks samples were prepared at different ratios as follows: I. FA1 contained FA70% + RS30%, II. FA2 contained FA60% + DW10%+RS30%, III. FA3 has a mix proportion of FA50% + DW20%+RS30%, IV. FA4 has a mix ratio FA40% + DW30%+RS30%, V. FA5 contained FA20% + DW40% + SF10%+RS30% by mass percentage of the FA material. However, utilization of this wastes in production of bricks, does not only produce a valuable commercial product that is cost effective, but also reduces a major waste disposal problem from the surrounding environment.

Keywords: bricks, dolomite, fly ash, industrial wastes

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11235 Seismic Hazard Assessment of Offshore Platforms

Authors: F. D. Konstandakopoulou, G. A. Papagiannopoulos, N. G. Pnevmatikos, G. D. Hatzigeorgiou

Abstract:

This paper examines the effects of pile-soil-structure interaction on the dynamic response of offshore platforms under the action of near-fault earthquakes. Two offshore platforms models are investigated, one with completely fixed supports and one with piles which are clamped into deformable layered soil. The soil deformability for the second model is simulated using non-linear springs. These platform models are subjected to near-fault seismic ground motions. The role of fault mechanism on platforms’ response is additionally investigated, while the study also examines the effects of different angles of incidence of seismic records on the maximum response of each platform.

Keywords: hazard analysis, offshore platforms, earthquakes, safety

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11234 A Biometric Template Security Approach to Fingerprints Based on Polynomial Transformations

Authors: Ramon Santana

Abstract:

The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.

Keywords: fingerprint, template protection, bio-cryptography, minutiae protection

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11233 Segregation Patterns of Trees and Grass Based on a Modified Age-Structured Continuous-Space Forest Model

Authors: Jian Yang, Atsushi Yagi

Abstract:

Tree-grass coexistence system is of great importance for forest ecology. Mathematical models are being proposed to study the dynamics of tree-grass coexistence and the stability of the systems. However, few of the models concentrates on spatial dynamics of the tree-grass coexistence. In this study, we modified an age-structured continuous-space population model for forests, obtaining an age-structured continuous-space population model for the tree-grass competition model. In the model, for thermal competitions, adult trees can out-compete grass, and grass can out-compete seedlings. We mathematically studied the model to make sure tree-grass coexistence solutions exist. Numerical experiments demonstrated that a fraction of area that trees or grass occupies can affect whether the coexistence is stable or not. We also tried regulating the mortality of adult trees with other parameters and the fraction of area trees and grass occupies were fixed; results show that the mortality of adult trees is also a factor affecting the stability of the tree-grass coexistence in this model.

Keywords: population-structured models, stabilities of ecosystems, thermal competitions, tree-grass coexistence systems

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11232 Constructing and Circulating Knowledge in Continuous Education: A Study of Norwegian Educational-Psychological Counsellors' Reflection Logs in Post-Graduate Education

Authors: Moen Torill, Rismark Marit, Astrid M. Solvberg

Abstract:

In Norway, every municipality shall provide an educational psychological service, EPS, to support kindergartens and schools in their work with children and youths with special needs. The EPS focus its work on individuals, aiming to identify special needs and to give advice to teachers and parents when they ask for it. In addition, the service also give priority to prevention and system intervention in kindergartens and schools. To master these big tasks university courses are established to support EPS counsellors' continuous learning. There is, however, a need for more in-depth and systematic knowledge on how they experience the courses they attend. In this study, EPS counsellors’ reflection logs during a particular course are investigated. The research question is: what are the content and priorities of the reflections that are communicated in the logs produced by the educational psychological counsellors during a post-graduate course? The investigated course is a credit course organized over a one-year period in two one-semester modules. The altogether 55 students enrolled in the course work as EPS counsellors in various municipalities across Norway. At the end of each day throughout the course period, the participants wrote reflection logs about what they had experienced during the day. The data material consists of 165 pages of typed text. The collaborating researchers studied the data material to ascertain, differentiate and understand the meaning of the content in each log. The analysis also involved the search for similarity in content and development of analytical categories that described the focus and primary concerns in each of the written logs. This involved constant 'critical and sustained discussions' for mutual construction of meaning between the co-researchers in the developing categories. The process is inspired by Grounded Theory. This means that the concepts developed during the analysis derived from the data material and not chosen prior to the investigation. The analysis revealed that the concept 'Useful' frequently appeared in the participants’ reflections and, as such, 'Useful' serves as a core category. The core category is described through three major categories: (1) knowledge sharing (concerning direct and indirect work with students with special needs) with colleagues is useful, (2) reflections on models and theoretical concepts (concerning students with special needs) are useful, (3) reflection on the role as EPS counsellor is useful. In all the categories, the notion of useful occurs in the participants’ emphasis on and acknowledgement of the immediate and direct link between the university course content and their daily work practice. Even if each category has an importance and value of its own, it is crucial that they are understood in connection with one another and as interwoven. It is the connectedness that gives the core category an overarching explanatory power. The knowledge from this study may be a relevant contribution when it comes to designing new courses that support continuing professional development for EPS counsellors, whether for post-graduate university courses or local courses at the EPS offices or whether in Norway or other countries in the world.

Keywords: constructing and circulating knowledge, educational-psychological counsellor, higher education, professional development

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11231 Non-Destructive Testing of Carbon Fiber Reinforced Plastic by Infrared Thermography Methods

Authors: W. Swiderski

Abstract:

Composite materials are one answer to the growing demand for materials with better parameters of construction and exploitation. Composite materials also permit conscious shaping of desirable properties to increase the extent of reach in the case of metals, ceramics or polymers. In recent years, composite materials have been used widely in aerospace, energy, transportation, medicine, etc. Fiber-reinforced composites including carbon fiber, glass fiber and aramid fiber have become a major structural material. The typical defect during manufacture and operation is delamination damage of layered composites. When delamination damage of the composites spreads, it may lead to a composite fracture. One of the many methods used in non-destructive testing of composites is active infrared thermography. In active thermography, it is necessary to deliver energy to the examined sample in order to obtain significant temperature differences indicating the presence of subsurface anomalies. To detect possible defects in composite materials, different methods of thermal stimulation can be applied to the tested material, these include heating lamps, lasers, eddy currents, microwaves or ultrasounds. The use of a suitable source of thermal stimulation on the test material can have a decisive influence on the detection or failure to detect defects. Samples of multilayer structure carbon composites were prepared with deliberately introduced defects for comparative purposes. Very thin defects of different sizes and shapes made of Teflon or copper having a thickness of 0.1 mm were screened. Non-destructive testing was carried out using the following sources of thermal stimulation, heating lamp, flash lamp, ultrasound and eddy currents. The results are reported in the paper.

Keywords: Non-destructive testing, IR thermography, composite material, thermal stimulation

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11230 Comparison of Applicability of Time Series Forecasting Models VAR, ARCH and ARMA in Management Science: Study Based on Empirical Analysis of Time Series Techniques

Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

Abstract:

Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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11229 Characterizing the Fracture Toughness Properties of Aluminum I-Rod Removed from National Research Universal Reactor

Authors: Michael Bach

Abstract:

Extensive weld repair was carried out in 2009 after a leak was detected in the aluminum 5052 vessel of the National Research Universal (NRU) reactor. This was the second vessel installed since 1974. In support of the NRU vessel leak repair and fitness for service assessments, an estimate of property changes due to irradiation exposure is required to extend the service of the reactor until 2018. In order to fully evaluate the property changes in the vessel wall, an Iodine-125 rod (I rod) made from the same material and irradiated in the NRU reactor from 1974 1991, was retrieved and sectioned for microstructure characterization and mechanical testing. The different sections of the I rod were exposed to various levels of thermal neutron fluences from 0 to a maximum of 11.9 x 1022 n/cm2. The end of life thermal neutron fluence of the NRU vessel is estimated to be 2.2 x 1022 n/cm2 at 35 years of service. Tensile test and fracture toughness test was performed on the I-rod material at various axial locations. The changes in tensile properties were attributed primarily to the creation of finely dispersed Mg-Si precipitates that harden the material and reduced the ductility. Despite having a reduction in fracture toughness, the NRU vessel is still operation at the current fluence levels.

Keywords: aluminum alloy, fitness-for-service assessment , fracutre toughness, nuclear reactor, precipitate strengthening, radiation damage, tensile strength

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11228 Hyperelastic Constitutive Modelling of the Male Pelvic System to Understand the Prostate Motion, Deformation and Neoplasms Location with the Influence of MRI-TRUS Fusion Biopsy

Authors: Muhammad Qasim, Dolors Puigjaner, Josep Maria López, Joan Herrero, Carme Olivé, Gerard Fortuny

Abstract:

Computational modeling of the human pelvis using the finite element (FE) method has become extremely important to understand the mechanics of prostate motion and deformation when transrectal ultrasound (TRUS) guided biopsy is performed. The number of reliable and validated hyperelastic constitutive FE models of the male pelvis region is limited, and given models did not precisely describe the anatomical behavior of pelvis organs, mainly of the prostate and its neoplasms location. The motion and deformation of the prostate during TRUS-guided biopsy makes it difficult to know the location of potential lesions in advance. When using this procedure, practitioners can only provide roughly estimations for the lesions locations. Consequently, multiple biopsy samples are required to target one single lesion. In this study, the whole pelvis model (comprised of the rectum, bladder, pelvic muscles, prostate transitional zone (TZ), and peripheral zone (PZ)) is used for the simulation results. An isotropic hyperelastic approach (Signorini model) was used for all the soft tissues except the vesical muscles. The vesical muscles are assumed to have a linear elastic behavior due to the lack of experimental data to determine the constants involved in hyperelastic models. The tissues and organ geometry is taken from the existing literature for 3D meshes. Then the biomechanical parameters were obtained under different testing techniques described in the literature. The acquired parametric values for uniaxial stress/strain data are used in the Signorini model to see the anatomical behavior of the pelvis model. The five mesh nodes in terms of small prostate lesions are selected prior to biopsy and each lesion’s final position is targeted when TRUS probe force of 30 N is applied at the inside rectum wall. Code_Aster open-source software is used for numerical simulations. Moreover, the overall effects of pelvis organ deformation were demonstrated when TRUS–guided biopsy is induced. The deformation of the prostate and neoplasms displacement showed that the appropriate material properties to organs altered the resulting lesion's migration parametrically. As a result, the distance traveled by these lesions ranged between 3.77 and 9.42 mm. The lesion displacement and organ deformation are compared and analyzed with our previous study in which we used linear elastic properties for all pelvic organs. Furthermore, the visual comparison of axial and sagittal slices are also compared, which is taken for Magnetic Resource Imaging (MRI) and TRUS images with our preliminary study.

Keywords: code-aster, magnetic resonance imaging, neoplasms, transrectal ultrasound, TRUS-guided biopsy

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11227 Use of SUDOKU Design to Assess the Implications of the Block Size and Testing Order on Efficiency and Precision of Dulce De Leche Preference Estimation

Authors: Jéssica Ferreira Rodrigues, Júlio Silvio De Sousa Bueno Filho, Vanessa Rios De Souza, Ana Carla Marques Pinheiro

Abstract:

This study aimed to evaluate the implications of the block size and testing order on efficiency and precision of preference estimation for Dulce de leche samples. Efficiency was defined as the inverse of the average variance of pairwise comparisons among treatments. Precision was defined as the inverse of the variance of treatment means (or effects) estimates. The experiment was originally designed to test 16 treatments as a series of 8 Sudoku 16x16 designs being 4 randomized independently and 4 others in the reverse order, to yield balance in testing order. Linear mixed models were assigned to the whole experiment with 112 testers and all their grades, as well as their partially balanced subgroups, namely: a) experiment with the four initial EU; b) experiment with EU 5 to 8; c) experiment with EU 9 to 12; and b) experiment with EU 13 to 16. To record responses we used a nine-point hedonic scale, it was assumed a mixed linear model analysis with random tester and treatments effects and with fixed test order effect. Analysis of a cumulative random effects probit link model was very similar, with essentially no different conclusions and for simplicity, we present the results using Gaussian assumption. R-CRAN library lme4 and its function lmer (Fit Linear Mixed-Effects Models) was used for the mixed models and libraries Bayesthresh (default Gaussian threshold function) and ordinal with the function clmm (Cumulative Link Mixed Model) was used to check Bayesian analysis of threshold models and cumulative link probit models. It was noted that the number of samples tested in the same session can influence the acceptance level, underestimating the acceptance. However, proving a large number of samples can help to improve the samples discrimination.

Keywords: acceptance, block size, mixed linear model, testing order, testing order

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11226 Supervised Machine Learning Approach for Studying the Effect of Different Joint Sets on Stability of Mine Pit Slopes Under the Presence of Different External Factors

Authors: Sudhir Kumar Singh, Debashish Chakravarty

Abstract:

Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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11225 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Authors: Soheila Sadeghi

Abstract:

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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11224 Churn Prediction for Savings Bank Customers: A Machine Learning Approach

Authors: Prashant Verma

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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

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11223 Stress Corrosion Cracking, Parameters Affecting It, Problems Caused by It and Suggested Methods for Treatment: State of the Art

Authors: Adnan Zaid

Abstract:

Stress corrosion cracking (SCC) may be defined as a degradation of the mechanical properties of a material under the combined action of a tensile stress and corrosive environment of the susceptible material. It is a harmful phenomenon which might cause catastrophic fracture without a sign of prior warning. In this paper, the stress corrosion cracking, SCC, process, the parameters affecting it, and the different damages caused by it are given and discussed. Utilization of shot peening as a mean of enhancing the resistance of materials to SCC is given and discussed. Finally, a method for improving materials resistance to SCC by grain refining its structure by some refining elements prior to usage is suggested.

Keywords: stress corrosion cracking, parameters, damages, treatment methods

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11222 Long-Term Deformations of Concrete Structures

Authors: Abdelmalk Brahma

Abstract:

Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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11221 A Digital Representation of a Microstructure and Determining Its Mechanical Behavior

Authors: Burak Bal

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Mechanical characterization tests might come with a remarkable cost of time and money for both companies and academics. The inquiry to transform laboratory experiments to the computational media is getting a trend; accordingly, the literature supplies many analytical ways to explain the mechanics of deformation. In our work, we focused on the crystal plasticity finite element modeling (CPFEM) analysis on various materials in various crystal structures to predict the stress-strain curve without tensile tests. For FEM analysis, which we used in this study was ABAQUS, a standard user-defined material subroutine (UMAT) was prepared. The geometry of a specimen was created via DREAM 3D software with the inputs of Euler angles taken by Electron Back-Scattered Diffraction (EBSD) technique as orientation, or misorientation angles. The synthetic crystal created with DREAM 3D is also meshed in a way the grains inside the crystal meshed separately, and the computer can realize interaction of inter, and intra grain structures. The mechanical deformation parameters obtained from the literature put into the Fortran based UMAT code to describe how material will response to the load applied from specific direction. The mechanical response of a synthetic crystal created with DREAM 3D agrees well with the material response in the literature.

Keywords: crystal plasticity finite element modeling, ABAQUS, Dream.3D, microstructure

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11220 An Elasto-Viscoplastic Constitutive Model for Unsaturated Soils: Numerical Implementation and Validation

Authors: Maria Lazari, Lorenzo Sanavia

Abstract:

Mechanics of unsaturated soils has been an active field of research in the last decades. Efficient constitutive models that take into account the partial saturation of soil are necessary to solve a number of engineering problems e.g. instability of slopes and cuts due to heavy rainfalls. A large number of constitutive models can now be found in the literature that considers fundamental issues associated with the unsaturated soil behaviour, like the volume change and shear strength behaviour with suction or saturation changes. Partially saturated soils may either expand or collapse upon wetting depending on the stress level, and it is also possible that a soil might experience a reversal in the volumetric behaviour during wetting. Shear strength of soils also changes dramatically with changes in the degree of saturation, and a related engineering problem is slope failures caused by rainfall. There are several states of the art reviews over the last years for studying the topic, usually providing a thorough discussion of the stress state, the advantages, and disadvantages of specific constitutive models as well as the latest developments in the area of unsaturated soil modelling. However, only a few studies focused on the coupling between partial saturation states and time effects on the behaviour of geomaterials. Rate dependency is experimentally observed in the mechanical response of granular materials, and a viscoplastic constitutive model is capable of reproducing creep and relaxation processes. Therefore, in this work an elasto-viscoplastic constitutive model for unsaturated soils is proposed and validated on the basis of experimental data. The model constitutes an extension of an existing elastoplastic strain-hardening constitutive model capable of capturing the behaviour of variably saturated soils, based on energy conjugated stress variables in the framework of superposed continua. The purpose was to develop a model able to deal with possible mechanical instabilities within a consistent energy framework. The model shares the same conceptual structure of the elastoplastic laws proposed to deal with bonded geomaterials subject to weathering or diagenesis and is capable of modelling several kinds of instabilities induced by the loss of hydraulic bonding contributions. The novelty of the proposed formulation is enhanced with the incorporation of density dependent stiffness and hardening coefficients in order to allow the modeling of the pycnotropy behaviour of granular materials with a single set of material constants. The model has been implemented in the commercial FE platform PLAXIS, widely used in Europe for advanced geotechnical design. The algorithmic strategies adopted for the stress-point algorithm had to be revised to take into account the different approach adopted by PLAXIS developers in the solution of the discrete non-linear equilibrium equations. An extensive comparison between models with a series of experimental data reported by different authors is presented to validate the model and illustrate the capability of the newly developed model. After the validation, the effectiveness of the viscoplastic model is displayed by numerical simulations of a partially saturated slope failure of the laboratory scale and the effect of viscosity and degree of saturation on slope’s stability is discussed.

Keywords: PLAXIS software, slope, unsaturated soils, Viscoplasticity

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11219 Steel Industry Waste as Recyclable Raw Material for the Development of Ferrous-Aluminum Alloys

Authors: Arnold S. Freitas Neto, Rodrigo E. Coelho, Erick S. Mendonça

Abstract:

The study aims to assess if high-purity iron powder in iron-aluminum alloys can be replaced by SAE 1020 steel chips with an atomicity proportion of 50% for each element. Chips of SAE 1020 are rejected in industrial processes. Thus, the use of SAE 1020 as a replaceable composite for iron increase the sustainability of ferrous alloys by recycling industrial waste. The alloys were processed by high energy milling, of which the main advantage is the minimal loss of raw material. The raw material for three of the six samples were high purity iron powder and recyclable aluminum cans. For the other three samples, the high purity iron powder has been replaced with chips of SAE 1020 steel. The process started with the separate milling of chips of aluminum and SAE 1020 steel to obtain the powder. Subsequently, the raw material was mixed in the pre-defined proportions, milled together for five hours and then underwent a closed-die hot compaction at the temperature of 500 °C. Thereafter, the compacted samples underwent heat treatments known as sintering and solubilization. All samples were sintered one hour, and 4 samples were solubilized for either 4 or 10 hours under well-controlled atmosphere conditions. Lastly, the composition and the mechanical properties of their hardness were analyzed. The samples were analyzed by optical microscopy, scanning electron microscopy and hardness testing. The results of the analysis showed a similar chemical composition and interesting hardness levels with low standard deviations. This verified that the use of SAE 1020 steel chips can be a low-cost alternative for high-purity iron powder and could possibly replace high-purity Iron in industrial applications.

Keywords: Fe-Al alloys, high energy milling, iron-aluminum alloys, metallography characterization, powder metallurgy, recycling ferrous alloy, SAE 1020 steel recycling

Procedia PDF Downloads 350
11218 Comparing Performance of Neural Network and Decision Tree in Prediction of Myocardial Infarction

Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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11217 Signs-Only Compressed Row Storage Format for Exact Diagonalization Study of Quantum Fermionic Models

Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko

Abstract:

The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.

Keywords: sparse matrix, compressed format, Hubbard model, Anderson model

Procedia PDF Downloads 389
11216 Optimizing the Passenger Throughput at an Airport Security Checkpoint

Authors: Kun Li, Yuzheng Liu, Xiuqi Fan

Abstract:

High-security standard and high efficiency of screening seem to be contradictory to each other in the airport security check process. Improving the efficiency as far as possible while maintaining the same security standard is significantly meaningful. This paper utilizes the knowledge of Operation Research and Stochastic Process to establish mathematical models to explore this problem. We analyze the current process of airport security check and use the M/G/1 and M/G/k models in queuing theory to describe the process. Then we find the least efficient part is the pre-check lane, the bottleneck of the queuing system. To improve passenger throughput and reduce the variance of passengers’ waiting time, we adjust our models and use Monte Carlo method, then put forward three modifications: adjust the ratio of Pre-Check lane to regular lane flexibly, determine the optimal number of security check screening lines based on cost analysis and adjust the distribution of arrival and service time based on Monte Carlo simulation results. We also analyze the impact of cultural differences as the sensitivity analysis. Finally, we give the recommendations for the current process of airport security check process.

Keywords: queue theory, security check, stochatic process, Monte Carlo simulation

Procedia PDF Downloads 194
11215 Application of Signature Verification Models for Document Recognition

Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

Abstract:

In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

Procedia PDF Downloads 138