Search results for: capillary effect model
26597 How Hormesis Impacts Practice of Ecological Risk Assessment and Food Safety Assessment
Authors: Xiaoxian Zhang
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Guidelines of ecological risk assessment (ERA) and food safety assessment (FSA) used nowadays, based on an S-shaped threshold dose-response curve (SDR), fail to consider hormesis, a reproducible biphasic dose-response model represented as a J-shaped or an inverted U-shaped curve, that occurs in the real-life environment across multitudinous compounds on cells, organisms, populations, and even the ecosystem. Specifically, in SDR-based ERA and FSA practice, predicted no effect concentration (PNEC) is calculated separately for individual substances from no observed effect concentration (NOEC, usually equivalent to 10% effect concentration (EC10) of a contaminant or food condiment) over an assessment coefficient that is bigger than 1. Experienced researchers doubted that hormesis in the real-life environment might lead to a waste of limited human and material resources in ERA and FSA practice, but related data are scarce. In this study, hormetic effects on bioluminescence of Aliivibrio fischeri (A. f) induced by sulfachloropyridazine (SCP) under 40 conditions to simulate the real-life scenario were investigated, and hormetic effects on growth of human MCF-7 cells caused by brown sugar and mascavado sugar were found likewise. After comparison of related parameters, it has for the first time been proved that there is a 50% probability for safe concentration (SC) of contaminants and food condiments to fall within the hormetic-stimulatory range (HSR) or left to HSR, revealing the unreliability of traditional parameters in standardized (eco)toxicological studies, and supporting qualitatively and quantitatively the over-strictness of ERA and FSA resulted from misuse of SDR. This study provides a novel perspective for ERA and FSA practitioners that hormesis should dominate and conditions where SDR works should only be singled out on a specific basis.Keywords: dose-response relationship, food safety, ecological risk assessment, hormesis
Procedia PDF Downloads 14626596 Improving Ride Comfort of a Bus Using Fuzzy Logic Controlled Suspension
Authors: Mujde Turkkan, Nurkan Yagiz
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In this study an active controller is presented for vibration suppression of a full-bus model. The bus is modelled having seven degrees of freedom. Using the achieved model via Lagrange Equations the system equations of motion are derived. The suspensions of the bus model include air springs with two auxiliary chambers are used. Fuzzy logic controller is used to improve the ride comfort. The numerical results, verifies that the presented fuzzy logic controller improves the ride comfort.Keywords: ride comfort, air spring, bus, fuzzy logic controller
Procedia PDF Downloads 43026595 Selection of Variogram Model for Environmental Variables
Authors: Sheikh Samsuzzhan Alam
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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 33426594 Mathematical Modeling of Activated Sludge Process: Identification and Optimization of Key Design Parameters
Authors: Ujwal Kishor Zore, Shankar Balajirao Kausley, Aniruddha Bhalchandra Pandit
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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 14426593 Rotor Radial Vent Pumping in Large Synchronous Electrical Machines
Authors: Darren Camilleri, Robert Rolston
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Rotor radial vents make use of the pumping effect to increase airflow through the active material thus reduce hotspot temperatures. The effect of rotor radial pumping in synchronous machines has been studied previously. This paper presents the findings of previous studies and builds upon their theories using a parametric numerical approach to investigate the rotor radial pumping effect. The pressure head generated by the poles and radial vent flow-rate were identified as important factors in maximizing the benefits of the pumping effect. The use of Minitab and ANSYS Workbench to investigate the key performance characteristics of radial pumping through a Design of Experiments (DOE) was described. CFD results were compared with theoretical calculations. A correlation for each response variable was derived through a statistical analysis. Findings confirmed the strong dependence of radial vent length on vent pressure head, and radial vent cross-sectional area was proved to be significant in maximising radial vent flow rate.Keywords: CFD, cooling, electrical machines, regression analysis
Procedia PDF Downloads 31226592 Conceptual Model for Knowledge Sharing Model in Creating Idea for Mobile Application
Authors: Hanafizan Hussain
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This study shows that several projects will be conducted at the workshop in which using the conceptual model for knowledge sharing approach to create an idea for mobile application. The sharing idea has been done through the collaborative activity in which a group of different field sought to define the mobile application which will lead to new media approach of using social media platform. The collaborative activity will be provided and implemented in the form of one day workshop to determine the approach towards the theme given. The activity later will be continued for four weeks for the participant to prepare for the pitch day workshop. This paper shows the pitch of idea including the interface and prototype for the said products. The collaboration between the members with different field of study shows that social media influenced the knowledge sharing model and its creation or innovations. One of the projects supported a collaborative activity in which a group of young designers sought to define the knowledge sharing model of their ability in creating idea for mobile applications.Keywords: mobile application, collaborative activity, conceptual knowledge sharing model, social media platform
Procedia PDF Downloads 14326591 Emergency Treatment of Methanol Poisoning: A Mathematical Approach
Authors: Priyanka Ghosh, Priti Kumar Roy
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Every year a considerable number of people die due to methyl alcohol poisoning, in which most of them die even before proper treatment. This work gives a simple and cheap first aid to those affected individuals by the administration of activated charcoal. In this article, we emphasise on the adsorption capability of activated charcoal for the treatment of poisoning and use an impulsive differential equation to study the effect of activated charcoal during adsorption. We also investigate the effects of various parameters on the adsorption which are incorporated in the model system.Keywords: activated charcoal, adsorption, impulsive differential equation, methanol poisoning
Procedia PDF Downloads 30826590 Dry Friction Occurring in the Suspensions for Passive and Switchable Damper Systems and Its Effect on Ride Comfort
Authors: Aref M. A. Soliman, Mahmoud A. Hassan
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In all vehicle suspension, there is a dry friction. One of the various active suspensions, which have been shown to have considerable practical potential, is a switchable damper suspension system. In this paper, vehicle ride comfort for the passive and switchable damper suspension systems as affected by the value of frictional force generated in springs is discussed. A mathematical model of a quarter vehicle model for two setting switchable damper suspension system with dry friction force is developed to evaluate vehicle ride comfort in terms of suspension performance criteria. The vehicle itself is treated as a rigid body undergoing vertical motions. Comparisons between passive and switchable damper suspensions systems with dry friction force in terms of ride performance are also discussed. The results showed that the ride comfort for the passive and switchable damper suspension systems was deteriorated due to dry friction occurring in the suspensions. The two setting switchable damper with and without dry friction force gives better ride improvements compared with the passive suspension system. Also, the obtained results show an optimum value of damping ratio of the passive suspension system.Keywords: ride comfort, dry friction, switchable damper, passive suspension
Procedia PDF Downloads 37226589 The Social Enterprise Model And Its Beneficiaries
Authors: Lorryn Williams
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This study will explore how the introduction of the for-profit social enterprise model affects the real lives of the individuals and communities that this model aims to help in South Africa. The congruence between organisational need construction and the real needs of beneficiaries, and whether the adoption of a profit driven model, such as social entrepreneurship, supports or discards these needs is key to answering the former question. By making use of qualitative methods, the study aims to collect empirical evidence that either supports the social entrepreneurship approach when compared to other programs such as vocational training programs or rejects it as less beneficial. It is the objective of this research to provide an answer to the question of whether the social enterprise model of conducting charity leaves the beneficiaries of non-profit organisations in a generally better or worse off position. The study will specifically explore the underlying assumptions the social entrepreneurship model makes, since the assumptions made concerning the uplifting effects it has on its beneficiaries may produce either real or assumed change for beneficiaries. The meaning of social cohesion and social capital for these organisations, the construction of beneficiary dependence and independence, the consideration of formal and informal economies beneficiaries engage in, and the extent to which sustainability is used as a brand, will be investigated. Through engaging the relevant literature, experts in the field of non-profit donorship and need implementation, organisations who have both adopted social enterprise programs and not, and most importantly, the beneficiaries themselves, it will be possible to provide answers to questions this study aims to answer.Keywords: social enterprise, beneficiaries, profit driven model, non-profit organizations
Procedia PDF Downloads 14026588 On Four Models of a Three Server Queue with Optional Server Vacations
Authors: Kailash C. Madan
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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.Keywords: a three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state
Procedia PDF Downloads 29626587 A Novel Algorithm for Parsing IFC Models
Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai
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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD). Procedia PDF Downloads 30026586 Expanding Trading Strategies By Studying Sentiment Correlation With Data Mining Techniques
Authors: Ved Kulkarni, Karthik Kini
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This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.Keywords: data mining, language processing, artificial neural networks, sentiment analysis
Procedia PDF Downloads 1726585 Modeling and Temperature Control of Water-cooled PEMFC System Using Intelligent Algorithm
Authors: Chen Jun-Hong, He Pu, Tao Wen-Quan
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Proton exchange membrane fuel cell (PEMFC) is the most promising future energy source owing to its low operating temperature, high energy efficiency, high power density, and environmental friendliness. In this paper, a comprehensive PEMFC system control-oriented model is developed in the Matlab/Simulink environment, which includes the hydrogen supply subsystem, air supply subsystem, and thermal management subsystem. Besides, Improved Artificial Bee Colony (IABC) is used in the parameter identification of PEMFC semi-empirical equations, making the maximum relative error between simulation data and the experimental data less than 0.4%. Operation temperature is essential for PEMFC, both high and low temperatures are disadvantageous. In the thermal management subsystem, water pump and fan are both controlled with the PID controller to maintain the appreciate operation temperature of PEMFC for the requirements of safe and efficient operation. To improve the control effect further, fuzzy control is introduced to optimize the PID controller of the pump, and the Radial Basis Function (RBF) neural network is introduced to optimize the PID controller of the fan. The results demonstrate that Fuzzy-PID and RBF-PID can achieve a better control effect with 22.66% decrease in Integral Absolute Error Criterion (IAE) of T_st (Temperature of PEMFC) and 77.56% decrease in IAE of T_in (Temperature of inlet cooling water) compared with traditional PID. In the end, a novel thermal management structure is proposed, which uses the cooling air passing through the main radiator to continue cooling the secondary radiator. In this thermal management structure, the parasitic power dissipation can be reduced by 69.94%, and the control effect can be improved with a 52.88% decrease in IAE of T_in under the same controller.Keywords: PEMFC system, parameter identification, temperature control, Fuzzy-PID, RBF-PID, parasitic power
Procedia PDF Downloads 8526584 Long- and Short-Term Impacts of COVID-19 and Gold Price on Price Volatility: A Comparative Study of MIDAS and GARCH-MIDAS Models for USA Crude Oil
Authors: Samir K. Safi
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The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility
Procedia PDF Downloads 6526583 Sphere in Cube Grid Approach to Modelling of Shale Gas Production Using Non-Linear Flow Mechanisms
Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic
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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.Keywords: adsorption, diffusion, non-linear flow, shale gas production
Procedia PDF Downloads 16626582 A Crystal Plasticity Approach to Model Dynamic Strain Aging
Authors: Burak Bal, Demircan Canadinc
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Dynamic strain aging (DSA), resulting from the reorientation of C-Mn clusters in the core of dislocations, can provide a strain hardening mechanism. In addition, in Hadfield steel, negative strain rate sensitivity is observed due to the DSA. In our study, we incorporated dynamic strain aging onto crystal plasticity computations to predict the local instabilities and corresponding negative strain rate sensitivity. Specifically, the material response of Hadfield steel was obtained from monotonic and strain-rate jump experiments under tensile loading. The strain rate range was adjusted from 10⁻⁴ to 10⁻¹s ⁻¹. The crystal plasticity modeling of the material response was carried out based on Voce-type hardening law and corresponding Voce hardening parameters were determined. The solute pinning effect of carbon atom was incorporated to crystal plasticity simulations at microscale level by computing the shear stress contribution imposed on an arrested dislocation by carbon atom. After crystal plasticity simulations with modifying hardening rule, which takes into account the contribution of DSA, it was seen that the model successfully predicts both the role of DSA and corresponding strain rate sensitivity.Keywords: crystal plasticity, dynamic strain aging, Hadfield steel, negative strain rate sensitivity
Procedia PDF Downloads 26026581 Genetic Algorithm for Bi-Objective Hub Covering Problem
Authors: Abbas Mirakhorli
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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm
Procedia PDF Downloads 6026580 3D Liver Segmentation from CT Images Using a Level Set Method Based on a Shape and Intensity Distribution Prior
Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang
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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method
Procedia PDF Downloads 31326579 Rating Agreement: Machine Learning for Environmental, Social, and Governance Disclosure
Authors: Nico Rosamilia
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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).Keywords: ESG ratings, non-financial information, value of firms, sustainable finance
Procedia PDF Downloads 8326578 AM/E/c Queuing Hub Maximal Covering Location Model with Fuzzy Parameter
Authors: M. H. Fazel Zarandi, N. Moshahedi
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The hub location problem appears in a variety of applications such as medical centers, firefighting facilities, cargo delivery systems and telecommunication network design. The location of service centers has a strong influence on the congestion at each of them, and, consequently, on the quality of service. This paper presents a fuzzy maximal hub covering location problem (FMCHLP) in which travel costs between any pair of nodes is considered as a fuzzy variable. In order to consider the quality of service, we model each hub as a queue. Arrival rate follows Poisson distribution and service rate follows Erlang distribution. In this paper, at first, a nonlinear mathematical programming model is presented. Then, we convert it to the linear one. We solved the linear model using GAMS software up to 25 nodes and for large sizes due to the complexity of hub covering location problems, and simulated annealing algorithm is developed to solve and test the model. Also, we used possibilistic c-means clustering method in order to find an initial solution.Keywords: fuzzy modeling, location, possibilistic clustering, queuing
Procedia PDF Downloads 39426577 ANSYS FLUENT Simulation of Natural Convection and Radiation in a Solar Enclosure
Authors: Sireetorn Kuharat, Anwar Beg
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In this study, multi-mode heat transfer characteristics of spacecraft solar collectors are investigated computationally. Two-dimensional steady-state incompressible laminar Newtonian viscous convection-radiative heat transfer in a rectangular solar collector geometry. The ANSYS FLUENT finite volume code (version 17.2) is employed to simulate the thermo-fluid characteristics. Several radiative transfer models are employed which are available in the ANSYS workbench, including the classical Rosseland flux model and the more elegant P1 flux model. Mesh-independence tests are conducted. Validation of the simulations is conducted with a computational Harlow-Welch MAC (Marker and Cell) finite difference method and excellent correlation. The influence of aspect ratio, Prandtl number (Pr), Rayleigh number (Ra) and radiative flux model on temperature, isotherms, velocity, the pressure is evaluated and visualized in color plots. Additionally, the local convective heat flux is computed and solutions are compared with the MAC solver for various buoyancy effects (e.g. Ra = 10,000,000) achieving excellent agreement. The P1 model is shown to better predict the actual influence of solar radiative flux on thermal fluid behavior compared with the limited Rosseland model. With increasing Rayleigh numbers the hot zone emanating from the base of the collector is found to penetrate deeper into the collector and rises symmetrically dividing into two vortex regions with very high buoyancy effect (Ra >100,000). With increasing Prandtl number (three gas cases are examined respectively hydrogen gas mixture, air and ammonia gas) there is also a progressive incursion of the hot zone at the solar collector base higher into the solar collector space and simultaneously a greater asymmetric behavior of the dual isothermal zones. With increasing aspect ratio (wider base relative to the height of the solar collector geometry) there is a greater thermal convection pattern around the whole geometry, higher temperatures and the elimination of the cold upper zone associated with lower aspect ratio.Keywords: thermal convection, radiative heat transfer, solar collector, Rayleigh number
Procedia PDF Downloads 11926576 Mediating Effect of Hopefulness on the Effect of Underdog Narratives to Subjective Well-Being among Local State University of Cavite
Authors: Quiza Pearl Senilla, Hannah Mercado, Francis Angelo Erosa
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Underdog narratives not only provides viewers with models of determination and hard work but that inducing hope may increase the likelihood that viewers will pursue their own goals in life. Although it has been proven that underdog narratives not only create a positive motivational state to the viewers but can also induce hope, little attention has been given to know if this underdog narrative affect the health outcomes or the subjective well-being of the viewers and if their hopefulness mediates on it. To address this gap, using underdog narratives as a predictor and hope as mediator, this study determined the effect of underdog narratives to the subjective well-being of the respondents, the relationship of hope and subjective well-being and last is the mediating effect of hopefulness. This study is an experimental research that uses a between subject design. Purposeful random sampling was used wherein the respondents must meet the following criteria to be part of the study. One hundred and twenty (N=120) Local State University students were assigned to different treatment conditions— underdog narrative, comedy, nature scenes—and a no exposure control group. Results show that there is a minimal difference on the subjective well-being of the respondents when exposed to different treatment condition although it is not significant. A moderate positive correlation between hope and subjective well-being also reveals in this study. And last the result also shows that there is no mediating effect of hopefulness to the subjective well-being of the subjects through exposure to underdog narrative.Keywords: hope, hope theory, subjective well-being, underdog narratives
Procedia PDF Downloads 31026575 The Study of Applying Models: House, Temple and School for Sufficiency Development to Participate in ASEAN Economic Community: A Case Study of Trimitra Temple (China Town) Bangkok, Thailand
Authors: Saowapa Phaithayawat
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The purposes of this study are: 1) to study the impact of the 3-community-core model: House (H), Temple (T), and School (S) with the co-operation of official departments on community development to ASEAN economic community involvement, and 2) to study the procedures and extension of the model. The research which is a qualitative research based on formal and informal interviews. Local people in a community are observed. Group interview is also operated by executors and cooperators in the school in the community. In terms of social and cultural dimension, the 3-community-core model consisting of house, temple and school is the base of Thai cultures bringing about understanding, happiness and unity to the community. The result of this research is that the official departments in accompanied with this model developers cooperatively work together in the community to support such factors as budget, plan, activities. Moreover, the need of community, and the continual result to sustain the community are satisfied by the model implementation. In terms of the procedures of the model implementation, executors and co-operators can work, coordinate, think, and launch their public relation altogether. Concerning the model development, this enables the community to achieve its goal to prepare the community’s readiness for ASEAN Economic Community involvement.Keywords: ASEAN Economic Community, the applying models and sufficiency development, house, temple, school
Procedia PDF Downloads 31426574 Cybernetic Modeling of Growth Dynamics of Debaryomyces nepalensis NCYC 3413 and Xylitol Production in Batch Reactor
Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi
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Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol
Procedia PDF Downloads 32826573 Modeling Studies on the Elevated Temperatures Formability of Tube Ends Using RSM
Authors: M. J. Davidson, N. Selvaraj, L. Venugopal
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The elevated temperature forming studies on the expansion of thin walled tubes have been studied in the present work. The influence of process parameters namely the die angle, the die ratio and the operating temperatures on the expansion of tube ends at elevated temperatures is carried out. The range of operating parameters have been identified by perfoming extensive simulation studies. The hot forming parameters have been evaluated for AA2014 alloy for performing the simulation studies. Experimental matrix has been developed from the feasible range got from the simulation results. The design of experiments is used for the optimization of process parameters. Response Surface Method’s (RSM) and Box-Behenken design (BBD) is used for developing the mathematical model for expansion. Analysis of variance (ANOVA) is used to analyze the influence of process parameters on the expansion of tube ends. The effect of various process combinations of expansion are analyzed through graphical representations. The developed model is found to be appropriate as the coefficient of determination value is very high and is equal to 0.9726. The predicted values are found to coincide well with the experimental results, within acceptable error limits.Keywords: expansion, optimization, Response Surface Method (RSM), ANOVA, bbd, residuals, regression, tube
Procedia PDF Downloads 50926572 A Quick Prediction for Shear Behaviour of RC Membrane Elements by Fixed-Angle Softened Truss Model with Tension-Stiffening
Authors: X. Wang, J. S. Kuang
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The Fixed-angle Softened Truss Model with Tension-stiffening (FASTMT) has a superior performance in predicting the shear behaviour of reinforced concrete (RC) membrane elements, especially for the post-cracking behaviour. Nevertheless, massive computational work is inevitable due to the multiple transcendental equations involved in the stress-strain relationship. In this paper, an iterative root-finding technique is introduced to FASTMT for solving quickly the transcendental equations of the tension-stiffening effect of RC membrane elements. This fast FASTMT, which performs in MATLAB, uses the bisection method to calculate the tensile stress of the membranes. By adopting the simplification, the elapsed time of each loop is reduced significantly and the transcendental equations can be solved accurately. Owing to the high efficiency and good accuracy as compared with FASTMT, the fast FASTMT can be further applied in quick prediction of shear behaviour of complex large-scale RC structures.Keywords: bisection method, FASTMT, iterative root-finding technique, reinforced concrete membrane
Procedia PDF Downloads 27126571 Effect of Concrete Waste Quality on the Compressive Strength of Recycled Concrete
Authors: Kebaili Bachir
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The reuse of concrete waste as a secondary aggregate could be an efficient solution for sustainable development and long-term environmental protection. The variable nature of waste concrete, with various compressive strengths, can have a negative effect on the final compressive strength of recycled concrete. Accordingly, an experimental test programme was developed to evaluate the effect of parent concrete qualities on the performance of recycled concrete. Three grades with different compressive strengths 10MPa, 20MPa, and 30MPa were considered in the study; moreover, an unknown compressive strength was introduced as well. The trial mixes used 40% secondary aggregates (both course and fine) and 60% of natural aggregates. The compressive strength of the test concrete decrease between 15 and 25% compared to normal concrete with no secondary aggregates. This work proves that the strength properties of the parent concrete have a limited effect on the compressive strength of recycled concrete. Low compressive strength parent concrete when crushed generate a high percentage of recycled coarse aggregates with the less attached mortar and give the same compressive strength as an excellent parent concrete. However, the decrease in compressive strength can be mitigated by increasing the cement content 4% by weight of recycled aggregates used.Keywords: compressive, concrete, quality, recycled, strength
Procedia PDF Downloads 32826570 Predictive Models of Ruin Probability in Retirement Withdrawal Strategies
Authors: Yuanjin Liu
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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model
Procedia PDF Downloads 7426569 Effect of Atmospheric Turbulence on Hybrid FSO/RF Link Availability under Qatar's Harsh Climate
Authors: Abir Touati, Syed Jawad Hussain, Farid Touati, Ammar Bouallegue
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Although there has been a growing interest in the hybrid free-space optical link and radio frequency FSO/RF communication system, the current literature is limited to results obtained in moderate or cold environment. In this paper, using a soft switching approach, we investigate the effect of weather inhomogeneities on the strength of turbulence hence the channel refractive index under Qatar harsh environment and their influence on the hybrid FSO/RF availability. In this approach, either FSO/RF or simultaneous or none of them can be active. Based on soft switching approach and a finite state Markov Chain (FSMC) process, we model the channel fading for the two links and derive a mathematical expression for the outage probability of the hybrid system. Then, we evaluate the behavior of the hybrid FSO/RF under hazy and harsh weather. Results show that the FSO/RF soft switching renders the system outage probability less than that of each link individually. A soft switching algorithm is being implemented on FPGAs using Raptor code interfaced to the two terminals of a 1Gbps/100 Mbps FSO/RF hybrid system, the first being implemented in the region. Experimental results are compared to the above simulation results.Keywords: atmospheric turbulence, haze, hybrid FSO/RF, outage probability, refractive index
Procedia PDF Downloads 41926568 Biosignal Recognition for Personal Identification
Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor
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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification
Procedia PDF Downloads 280