Search results for: Flow-3D numerical model

Authors: Belyayev P. E., Makeyeva I. R., Mastyuk D. A., Pigasov E. E.

Abstract:

Previously, the phrase ”hydrogen safety” was often used in terms of NPP safety. Due to the rise of interest to “green” and, particularly, hydrogen power engineering, the problem of hydrogen safety at industrial facilities has become ever more urgent. In Russia, the industrial production of hydrogen is meant to be performed by placing a chemical engineering plant near NPP, which supplies the plant with the necessary energy. In this approach, the production of hydrogen involves a wide range of combustible gases, such as methane, carbon monoxide, and hydrogen itself. Considering probable incidents, sudden combustible gas outburst into open space with further ignition is less dangerous by itself than ignition of the combustible mixture in the presence of many pipelines, reactor vessels, and any kind of fitting frames. Even ignition of 2100 cubic meters of the hydrogen-air mixture in open space gives velocity and pressure that are much lesser than velocity and pressure in Chapman-Jouguet condition and do not exceed 80 m/s and 6 kPa accordingly. However, the space blockage, the significant change of channel diameter on the way of flame propagation, and the presence of gas suspension lead to significant deflagration acceleration and to its transition into detonation or quasi-detonation. At the same time, process parameters acquired from the experiments at specific experimental facilities are not general, and their application to different facilities can only have a conventional and qualitative character. Yet, conducting deflagration and detonation experimental investigation for each specific industrial facility project in order to determine safe infrastructure unit placement does not seem feasible due to its high cost and hazard, while the conduction of numerical experiments is significantly cheaper and safer. Hence, the development of a numerical method that allows the description of reacting flows in domains with complex geometry seems promising. The base for this method is the modification of Kuropatenko method for calculating shock waves recently developed by authors, which allows using it in Eulerian coordinates. The current work contains the results of the development process. In addition, the comparison of numerical simulation results and experimental series with flame propagation in shock tubes with orifice plates is presented.

Keywords: CFD, reacting flow, DDT, gas explosion

Procedia PDF Downloads 90

Authors: Chanh Nghia Nguyen, Yu Kurokawa, Hirotsugu Inoue

Abstract:

The surface roughness is an important parameter for evaluating the quality of material surfaces since it affects functions and performance of industrial components. Although stylus and optical techniques are commonly used for measuring the surface roughness, they are applicable only to accessible surfaces. In practice, surface roughness measurement from the back side is sometimes demanded, for example, in inspection of safety-critical parts such as inner surface of pipes. However, little attention has been paid to the measurement of back surface roughness so far. Since back surface is usually inaccessible by stylus or optical techniques, ultrasonic technique is one of the most effective among others. In this research, an ultrasonic pulse-echo technique is considered for evaluating the pitch and the height of back surface having periodic triangular profile as a very first step. The pitch of the surface profile is measured by applying the diffraction grating theory for oblique incidence; then the height is evaluated by numerical analysis based on the Kirchhoff theory for normal incidence. The validity of the proposed method was verified by both numerical simulation and experiment. It was confirmed that the pitch is accurately measured in most cases. The height was also evaluated with good accuracy when it is smaller than a half of the pitch because of the approximation in the Kirchhoff theory.

Keywords: back side, inaccessible surface, periodic roughness, pulse-echo technique, ultrasonic NDE

Procedia PDF Downloads 275

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

Procedia PDF Downloads 438

Authors: Sujit K. Basak

Abstract:

The aim of this paper is to analyze the impact of literature review software on researchers. The aim of this study was achieved by analyzing models in terms of perceived usefulness, perceived ease of use, and acceptance level. Collected data was analyzed using WarpPLS 4.0 software. This study used two theoretical frameworks namely Technology Acceptance Model and the Training Needs Assessment Model. The study was experimental and was conducted at a public university in South Africa. The results of the study showed that acceptance level has a high impact on research workload and productivity followed by perceived usefulness and perceived ease of use.

Keywords: technology acceptance model, training needs assessment model, literature review software, research productivity

Procedia PDF Downloads 505

Authors: Yin-Yee Leong, Jack C. Yue, Hsin-Chung Wang

Abstract:

Human longevity has been experiencing its largest increase since the end of World War II, and modeling the mortality rates is therefore often the focus of many studies. Among all mortality models, the Lee–Carter model is the most popular approach since it is fairly easy to use and has good accuracy in predicting mortality rates (e.g., for Japan and the USA). However, empirical studies from several countries have shown that the age parameters of the Lee–Carter model are not constant in time. Many modifications of the Lee–Carter model have been proposed to deal with this problem, including adding an extra cohort effect and adding another period effect. In this study, we propose a spatial modification and use clusters to explain why the age parameters of the Lee–Carter model are not constant. In spatial analysis, clusters are areas with unusually high or low mortality rates than their neighbors, where the “location” of mortality rates is measured by age and time, that is, a 2-dimensional coordinate. We use a popular cluster detection method—Spatial scan statistics, a local statistical test based on the likelihood ratio test to evaluate where there are locations with mortality rates that cannot be described well by the Lee–Carter model. We first use computer simulation to demonstrate that the cluster effect is a possible source causing the problem of the age parameters not being constant. Next, we show that adding the cluster effect can solve the non-constant problem. We also apply the proposed approach to mortality data from Japan, France, the USA, and Taiwan. The empirical results show that our approach has better-fitting results and smaller mean absolute percentage errors than the Lee–Carter model.

Keywords: mortality improvement, Lee–Carter model, spatial statistics, cluster detection

Procedia PDF Downloads 172

Authors: Munazza A. Mirza, Khawar Khurshid

Abstract:

Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: learning style, VARK, sensory preferences, identification model, didactic practices

Procedia PDF Downloads 281

Authors: Leon Pan

Abstract:

The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

Procedia PDF Downloads 60

Authors: Nermin Sökmen

Abstract:

An effort estimation model is needed for software-intensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis

Procedia PDF Downloads 294

Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

Abstract:

This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges

Procedia PDF Downloads 164

Authors: Osamu Komori, Shinto Eguchi, Hiroshi Okamura, Momoko Ichinokawa

Abstract:

The long time-series data on population assessments are essential for global ecosystem assessment because the temporal change of biomass in such a database reflects the status of global ecosystem properly. However, the available assessment data usually have limited sample sizes and the ratio of populations with low abundance of biomass (collapsed) to those with high abundance (non-collapsed) is highly imbalanced. To allow for the imbalance and uncertainty involved in the ecological data, we propose a binary regression model with mixed effects for inferring ecosystem status through an asymmetric logistic model. In the estimation equation, we observe that the weights for the non-collapsed populations are relatively reduced, which in turn puts more importance on the small number of observations of collapsed populations. Moreover, we extend the asymmetric logistic regression model using propensity score to allow for the sample biases observed in the labeled and unlabeled datasets. It robustified the estimation procedure and improved the model fitting.

Keywords: double robust estimation, ecological binary data, mixed effect logistic regression model, propensity score

Procedia PDF Downloads 268

Authors: Habibullah Pathan

Abstract:

The present study aims to explore problems faced by English Language Teachers (ELT) while implementing the Outcome Based Education (OBE) model in engineering universities of Sindh. OBE is an emerging model initiative of the International Engineering Alliance. Traditional educational systems are teacher-centered or curriculum-centered, in which learners are not able to achieve desired outcomes, but the OBE model enables learners to know the outcomes before the start of the program. OBE is a circular process that begins from the needs and demands of society to stakeholders who ask the experts to produce the alumnus who can fulfill the needs and ends up getting new enrollment in the respective programs who can work according to the demands. In all engineering institutions, engineering courses besides English language courses are taught on the OBE model. English language teachers were interviewed to learn the in-depth of the problems faced by them. The study found that teachers were facing problems including pedagogical, OBE training, assessment, evaluation and administrative support. This study will be a guide for public and private English language teachers to cope with these challenges while teaching the English language on the OBE model. OBE is an emerging model by which the institutions can produce such a product that can meet the demands.

Keywords: problems of ELT teachers, outcome based education (OBE), implementing, assessment

Procedia PDF Downloads 99

Authors: Cleyton S. Stampa

Abstract:

This paper addresses the perspectives of using low melting point metals (LMPMs) as phase change materials (PCMs) in latent thermal energy storage (LTES) units, through a numerical approach. This is a new class of PCMs that has been one of the most prospective alternatives to be considered in LTES, due to these materials present high thermal conductivity and elevated heat of fusion, per unit volume. The chosen type of LTES consists of several horizontal parallel slabs filled with PCM. The heat transfer fluid (HTF) circulates through the channel formed between each two consecutive slabs on a laminar regime through forced convection. The study deals with the LTES charging process (heat-storing) by using pure gallium as PCM, and it considers heat conduction in the solid phase during melting driven by natural convection in the melt. The transient heat transfer problem is analyzed in one arbitrary slab under the influence of the HTF. The mathematical model to simulate the isothermal phase change is based on a volume-averaged enthalpy method, which is successfully verified by comparing its predictions with experimental data from works available in the pertinent literature. Regarding the convective heat transfer problem in the HTF, it is assumed that the flow is thermally developing, whereas the velocity profile is already fully developed. The study aims to learn about the effect of the solid subcooling in the melting rate through comparisons with the melting process of the solid in which it starts to melt from its fusion temperature. In order to best understand this effect in a metallic compound, as it is the case of pure gallium, the study also evaluates under the same conditions established for the gallium, the melting process of commercial paraffin wax (organic compound) and of the calcium chloride hexahydrate (CaCl₂ 6H₂O-inorganic compound). In the present work, it is adopted the best options that have been established by several researchers in their parametric studies with respect to this type of LTES, which lead to high values of thermal efficiency. To do so, concerning with the geometric aspects, one considers a gap of the channel formed by two consecutive slabs, thickness and length of the slab. About the HTF, one considers the type of fluid, the mass flow rate, and inlet temperature.

Keywords: flat slab, heat storing, pure metal, solid subcooling

Procedia PDF Downloads 141

Authors: A. Bogdanovic, M. Vitanova, J. Bojadjieva, Z. Rakicevic, V. Sesov, K. Edip, N. Naumovski, F. Manojlovski, A.Popovska, A. Shoklarovski, T. Kitanovski, D. Ivanovski, I. Markovski, D. Filipovski

Abstract:

The conditions of existing structures change in the course of time and can hardly be characterized particularly if a bridge has long been in function and there is no design documentation related to it. To define the real conditions of a structure, detailed static and dynamic analysis of the structure has to be carried out and its modal parameters have to be defined accurately. Modal analysis enables a quite accurate identification of the natural frequencies and mode shapes. Presented in this paper are the results from the performed detailed analyses of a steel truss bridge that has been in use for more than 7 decades by the military services of R.N. Macedonia and for which there is no documentation at all. Static and dynamic investigations and ambient vibration measurements were performed. The acquired data were used to identify the mode shapes that were used for comparison with the numerical model. Dynamic tests were performed to define the bridge behaviour and the damping index. Finally, based on all the conducted detailed analyses and investigations, conclusions on the conditions of the bridge structure were drawn.

Keywords: ambient vibrations, dynamic identification, in-situ measurement, steel truss bridge

Procedia PDF Downloads 93

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

Abstract:

Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling.

Keywords: groundwater model, geostatistics, pilot point, parameterization step

Procedia PDF Downloads 167

Authors: Ming Wen, Nasim Nezamoddini

Abstract:

Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

Procedia PDF Downloads 114

Authors: Wadsana Sarakarn, Pimonpan Charoensri, Baliya Chaiyara

Abstract:

Objectives: To study the outcomes of the developed nursing model to prevent early postpartum hemorrhage (PPH). Materials and Methods: The analytical study was conducted in Sunpasitthiprasong Hospital during October 1st, 2015, until May 31st, 2017. After review the prevalence, risk factors, and outcomes of postpartum hemorrhage of the parturient who gave birth in Sunpasitthiprasong Hospital, the nursing model was developed under research regulation of Kemmis&McTaggart using 4 steps of operating procedures: 1) analyzing problem situation and gathering 2) creating the plan 3) noticing and performing 4) reflecting the result of the operation. The nursing model consisted of the screening tools for risk factors associated with PPH, the clinical nursing practice guideline (CNPG), and the collecting bag for measuring postpartum blood loss. Primary outcome was early postpartum hemorrhage. Secondary outcomes were postpartum hysterectomy, maternal mortality, personnel’s practice, knowledge, and satisfaction of the nursing model. The data were analyzed by using content analysis for qualitative data and descriptive statistics for quantitative data. Results: Before using the nursing model, the prevalence of early postpartum hemorrhage was under estimated (2.97%). There were 5 cases of postpartum hysterectomy and 2 cases of maternal death due to postpartum hemorrhage. During the study period, there was 22.7% prevalence of postpartum hemorrhage among 220 pregnant women who were vaginally delivered at Sunpasitthiprasong Hospital. No maternal death or postpartum hysterectomy was reported after using the nursing model. Among 16 registered nurses at the delivery room who evaluated using of the nursing model, they reported the high level of practice, knowledge, and satisfaction Conclusion: The nursing model for the prevention of early PPH is effective to decrease early PPH and other serious complications.

Keywords: the development of a nursing model, prevention of postpartum hemorrhage, pregnant women, postpartum hemorrhage

Procedia PDF Downloads 99

Authors: Mahdad M’hamed, Belaidi Idir

Abstract:

This paper develops a meshless approach, called Element Free Galerkin (EFG) method, which is based on the weak form Moving Least Squares (MLS) of the partial differential governing equations and employs the interpolation to construct the meshless shape functions. The variation weak form is used in the EFG where the trial and test functions are approximated bye the MLS approximation. Since the shape functions constructed by this discretization have the weight function property based on the randomly distributed points, the essential boundary conditions can be implemented easily. The local weak form of the partial differential governing equations is obtained by the weighted residual method within the simple local quadrature domain. The spline function with high continuity is used as the weight function. The presently developed EFG method is a truly meshless method, as it does not require the mesh, either for the construction of the shape functions, or for the integration of the local weak form. Several numerical examples of two-dimensional static structural analysis are presented to illustrate the performance of the present EFG method. They show that the EFG method is highly efficient for the implementation and highly accurate for the computation. The present method is used to analyze the static deflection of beams and plate hole

Keywords: numerical computation, element-free Galerkin (EFG), moving least squares (MLS), meshless methods

Procedia PDF Downloads 283

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 89

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 70

Authors: Alena Zemanová, Jan Zeman, Michal Šejnoha

Abstract:

The polymer foil used for manufacturing of laminated glass members behaves in a viscoelastic manner with temperature dependence. This contribution aims at incorporating the time/temperature-dependent behavior of interlayer to our earlier elastic finite element model for laminated glass beams. The model is based on a refined beam theory: each layer behaves according to the finite-strain shear deformable formulation by Reissner and the adjacent layers are connected via the Lagrange multipliers ensuring the inter-layer compatibility of a laminated unit. The time/temperature-dependent behavior of the interlayer is accounted for by the generalized Maxwell model and by the time-temperature superposition principle due to the Williams, Landel, and Ferry. The resulting system is solved by the Newton method with consistent linearization and the viscoelastic response is determined incrementally by the exponential algorithm. By comparing the model predictions against available experimental data, we demonstrate that the proposed formulation is reliable and accurately reproduces the behavior of the laminated glass units.

Keywords: finite element method, finite-strain Reissner model, Lagrange multipliers, generalized Maxwell model, laminated glass, Newton method, Williams-Landel-Ferry equation

Procedia PDF Downloads 433

Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

Abstract:

The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

Procedia PDF Downloads 153

Authors: Mohammed Ali Hjaji, Magdi Mohareb

Abstract:

This paper develops the exact solutions for coupled flexural-lateral-torsional static response of thin-walled asymmetric open members subjected to general loading. Using the principle of stationary total potential energy, the governing differential equations of equilibrium are formulated as well as the associated boundary conditions. The formulation is based on a generalized Timoshenko-Vlasov beam theory and accounts for the effects of shear deformation due to bending and warping, and captures the effects of flexural–torsional coupling due to cross-section asymmetry. Closed-form solutions are developed for cantilever and simply supported beams under various forces. In order to demonstrate the validity and the accuracy of this solution, numerical examples are presented and compared with well-established ABAQUS finite element solutions and other numerical results available in the literature. In addition, the results are compared against non-shear deformable beam theories in order to demonstrate the shear deformation effects.

Keywords: asymmetric cross-section, flexural-lateral-torsional response, Vlasov-Timoshenko beam theory, closed form solution

Procedia PDF Downloads 470

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: model predictive control, optimal control, process control, crystal growth

Procedia PDF Downloads 359

Authors: Faezeh Shalchy

Abstract:

Concrete is the most used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, concrete is weak in tension, over the past thirty years many studies were accomplished to improve the tensile properties of concrete (cement-based materials) using a variety of methods. One of the most successful attempts is to use polymeric fibers in the structure of concrete to obtain a composite with high tensile strength and ductility. Understanding the mechanical behavior of fiber reinforced concrete requires the knowledge of the fiber/matrix interfaces at the small scale. In this study, a combination of numerical simulations and experimental techniques have been used to study the nano structure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analysis. The adhesion energy between the C-S-H gel and 2 different polymeric fibers (polyvinyl alcohol and polypropylene) was numerically studied at the atomistic level since adhesion is one of the key factors in the design of fiber reinforced composites. The mechanisms of adhesion as a function of the nano structure of fiber/matrix interfaces are also studied and discussed.

Keywords: fiber-reinforced concrete, adhesion, molecular modeling

Procedia PDF Downloads 328

Authors: Hyo Lim Kang, Tae An Kim, Seung Ho Han

Abstract:

A 3-way reversing valve has been used in automotive washing machines to remove remaining oil and dirt on machined engine and transmission blocks. It provides rapid and accurate changes of water flow direction without any precise control device. However, due to its complicated bottom-plug shape, a cavitation occurs in a wide range of the bottom-plug in a downstream. In this study, the cavitation index and POC (percent of cavitation) were used to evaluate quantitatively the cavitation phenomena occurring at the bottom-plug. An optimal shape design was carried out via parametric study for geometries of the bottom-plug, in which a simple CAE-model was used in order to avoid time-consuming CFD analysis and hard to achieve convergence. To verify the results of numerical analysis, a flow visualization test was carried out using a test specimen with a transparent acryl pipe according to ISA-RP75.23. The flow characteristics such as the cavitation occurring in the downstream were investigated by using a flow test equipment with valve and pump including a flow control system and high-speed camera.

Keywords: cavitation, flow visualization test, optimal shape design, percent of cavitation, reversing valve

Procedia PDF Downloads 303

Authors: Sheikh Samsuzzhan Alam

Abstract:

The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

Procedia PDF Downloads 335

Authors: Ujwal Kishor Zore, Shankar Balajirao Kausley, Aniruddha Bhalchandra Pandit

Abstract:

There are some important design parameters of activated sludge process (ASP) for wastewater treatment and they must be optimally defined to have the optimized plant working. To know them, developing a mathematical model is a way out as it is nearly commensurate the real world works. In this study, a mathematical model was developed for ASP, solved under activated sludge model no 1 (ASM 1) conditions and MATLAB tool was used to solve the mathematical equations. For its real-life validation, the developed model was tested for the inputs from the municipal wastewater treatment plant and the results were quite promising. Additionally, the most cardinal assumptions required to design the treatment plant are discussed in this paper. With the need for computerization and digitalization surging in every aspect of engineering, this mathematical model developed might prove to be a boon to many biological wastewater treatment plants as now they can in no time know the design parameters which are required for a particular type of wastewater treatment.

Keywords: waste water treatment, activated sludge process, mathematical modeling, optimization

Procedia PDF Downloads 145

Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

Abstract:

The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

Procedia PDF Downloads 458

Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

Abstract:

This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

Procedia PDF Downloads 72

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

Abstract:

Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 85