Search results for: shared parameter model

Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

Procedia PDF Downloads 88

Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

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Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to the ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental mesoscale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to those obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, sensitivity analysis, total petroleum hydrocarbons

Procedia PDF Downloads 217

Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

Procedia PDF Downloads 374

Authors: Zhou Jianhong

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Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

Procedia PDF Downloads 520

Authors: R. Pilafkan, M. Kaffash Irzarahimi, S. F. Asbaghian Namin

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The biaxial buckling behavior of single-layered graphene sheets (SLGSs) is studied in the present work. To consider the size-effects in the analysis, Eringen’s nonlocal elasticity equations are incorporated into classical plate theory (CLPT). A Generalized Differential Quadrature Method (GDQM) approach is utilized and numerical solutions for the critical buckling loads are obtained. Then, molecular dynamics (MD) simulations are performed for a series of zigzag SLGSs with different side-lengths and with various boundary conditions, the results of which are matched with those obtained by the nonlocal plate model to numerical the appropriate values of nonlocal parameter relevant to each type of boundary conditions.

Keywords: biaxial buckling, single-layered graphene sheets, nonlocal elasticity, molecular dynamics simulation, classical plate theory

Procedia PDF Downloads 278

Authors: Semayat Fanta, P.M. Mohite, C.S. Upadhyay

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Damage meso-model for laminates is one of the most widely applicable approaches for the analysis of damage induced in laminated fiber-reinforced polymeric composites. Damage meso-model for laminates has been developed over the last three decades by many researchers in experimental, theoretical, and analytical methods that have been carried out in micromechanics as well as meso-mechanics analysis approaches. It has been fundamentally developed based on the micromechanical description that aims to predict the damage initiation and evolution until the failure of structure in various loading conditions. The current damage meso-model for laminates aimed to act as a bridge between micromechanics and macro-mechanics of the laminated composite structure. This model considers two meso-constituents for the analysis of damage in ply and interface that imparted from low-velocity impact. The damages considered in this study include fiber breakage, matrix cracking, and diffused damage of the lamina, and delamination of the interface. The damage initiation and evolution in laminae can be modeled in terms of damaged strain energy density using damage parameters and the thermodynamic irreversible forces. Interface damage can be modeled with a new concept of spherical micro-void in the resin-rich zone of interface material. The damage evolution is controlled by the damage parameter (d) and the radius of micro-void (r) from the point of damage nucleation to its saturation. The constitutive martial model for meso-constituents is defined in a user material subroutine VUMAT and implemented in ABAQUS/Explicit finite element modeling tool. The model predicts the damages in the meso-constituents level very accurately and is considered the most effective technique of modeling low-velocity impact simulation for laminated composite structures.

Keywords: mesomodel, laminate, low-energy impact, micromechanics

Procedia PDF Downloads 223

Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Debajyoti Choudhuri, Ratan Kumar Giri, Shesadev Pradhan

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The perturbed nonlinear Schrodinger equation involving the p-biharmonic and the p-Laplacian operators involving a real valued parameter and a continuous real valued potential function defined over the N- dimensional Euclidean space has been considered. By the variational technique, an existence result pertaining to a nontrivial solution to this non-linear partial differential equation has been proposed. Further, by the Concentration lemma, the concentration of solutions to the same problem defined on the set consisting of those elements where the potential function vanishes as the real parameter approaches to infinity has been addressed.

Keywords: p-Laplacian, p-biharmonic, elliptic PDEs, Concentration lemma, Sobolev space

Procedia PDF Downloads 236

Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

Procedia PDF Downloads 48

Authors: A. Abdikian

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Using the linearized quantum hydrodynamic model (QHD) and by considering the role of quantum parameter (Bohm’s potential) and electron exchange-correlation potential in conjunction with Maxwell’s equations, electromagnetic wave propagation in a single-walled carbon nanotubes was studied. The electronic excitations are described. By solving the mentioned equations with appropriate boundary conditions and by assuming the low-frequency electromagnetic waves, two general expressions of dispersion relations are derived for the transverse magnetic (TM) and transverse electric (TE) modes, respectively. The dispersion relations are analyzed numerically and it was found that the dependency of dispersion curves with the exchange-correlation effects (which have been ignored in previous works) in the low frequency would be limited. Moreover, it has been realized that asymptotic behaviors of the TE and TM modes are similar in single wall carbon nanotubes (SWCNTs). The results show that by adding the function of electron exchange-correlation potential lead to the phenomena and make to extend the validity range of QHD model. The results can be important in the study of collective phenomena in nanostructures.

Keywords: transverse magnetic, transverse electric, quantum hydrodynamic model, electron exchange-correlation potential, single-wall carbon nanotubes

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Authors: David E. Wilkins

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While colonialism in its many guises remains the dominant theoretical framework within which to analyze Indigenous relations with state powers, this paper takes a deep look at the treaty, policy, and statutory efforts initiated by both Indigenous peoples and colonial, and later federal representatives within what is now the United States that were intended to create a Native constituent state of the union. While these plans ultimately failed, they are indicative of the reality that, throughout much of the shared Indigenous and American history, there were both Native and non-Native political elites who were keen on the idea of incorporating Indigenous peoples into the burgeoning body politic. This paper explores why these plans arose, who the architects were that devised them, which Native peoples were involved in, and why they ultimately failed to be enacted. Although governmental relations within the US remain fraught and unpredictable, Native nations continue to wield a form of sovereignty that, while truncated, has maintained their distinctive political statuses. There is much to be learned from the exploration of these mixed successes and failures. There are other examples across the globe whereby Indigenous peoples like the Saami and the Māori have secured greater clarity of their retained autonomy through structural political arrangements with the states that have laid claim to their territories while the Ainu struggle to regain their status.

Keywords: indigenous, sovereignty, diplomacy, intergovernmental

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Authors: Faduma Ahmed-Ali

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The up and coming new generation of travelers will change how the world will achieve its global connectivity. The goal is that through people and technological advancement world-wide, people will be able to better explore the culture and beauty, as well as gain a better understanding of the core values of each host countries treasures. Through Rika's unique world connection model approach, the tourist can explore their destination with the help of local connections. Achieving a complete understanding of the host country while ensuring equal economic prosperity and cultural exchange is key to changing the face of tourism. A recent survey conducted by the author at Portland International Airport shows that over 50% of tourists entering Portland, Oregon are more eager to explore the city through local residents rather than an already planned itinerary created by travel companies. This new model, Rika, aims to shed light to the importance of connecting tourists with the technological tools that increase connectivity to the locals for a better travel experience and that fosters shared economic prosperity throughout a community achieving the goal of creating a sustainable, people driven economy.

Keywords: RIKA, tourism, connection, technology, economic impact, sustainability, hospitality, strategies, tourism development, environment

Procedia PDF Downloads 286

Authors: Gabriel Sunday Ayayia

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The paper argues that Ubuntu, as a philosophy that emphasizes the interconnectedness of all living things and importance of community and mutual support, can be used as a social framework to address the problems of climate change and promote environmental sustainability. The research demonstrate that Ubuntu is an ideological concept that encourages collective action on climate change, with the emphasis on individual and collective commitment to taking concrete action to address the problems of climate change. The paper shows that Ubuntu can be employed as a social tool that would enhance the cultivation of shared identity and promote the sense of shared response responsibility to develop the resilience to cope with climate change. Using qualitative and quantitative methodologies, the study establishes the imperativeness of mutual support and cooperation through the lens of Ubuntu as a human-centered scalable response to the debacle of climate change. It recommends that we can build a society that values the environment and promotes sustainable practices by encouraging community involvement in sustainable initiatives by integrating Ubuntu-based principles to our decision-making processes, collaboration, leadership, human agency and governance.

Keywords: ubuntu, climate change, humanity, collective actions, community-based

Procedia PDF Downloads 188

Authors: Hamed Bagheri, Seyd Javid Shariati

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The effects of type and amount of solvent on lubricant which is used in disposable medical devices are investigated in this article. Two kinds of common solvent, n-Hexane and n-Heptane, are used. The mechanical behavior of syringe has shown that n-Heptane has better mixing ratio and also more effective spray process in the barrel of syringe than n-Hexane because of similar solubility parameter to silicon oil. The results revealed that movement of plunger in the barrel increases when pure silicone is used because non-uniform film is created on the surface of barrel, and also, it seems that the form of silicon is converted from oil to gel due to sterilization process. The results showed that the convenient mixing ratio of solvent/lubricant oil is 80/20.

Keywords: disposal medical devices, lubricant oil, solvent effect, solubility parameter

Procedia PDF Downloads 232

Authors: Shobha G. Ranjan

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Cloud computing is an emerging, on-demand and internet- based technology. Varieties of services like, software, hardware, data storage and infrastructure can be shared though the cloud computing. This technology is highly reliable, cost effective and scalable in nature. It is a must only the authorized users should access these services. Further the time granted to access these services should be taken into account for proper accounting purpose. Currently many organizations do the security measures in many different ways to provide the best cloud infrastructure to their clients, but that’s not the limitation. This paper presents the multi-level security measure technique which is in accordance with the OSI model. In this paper, details of proposed multilevel security measures technique are presented along with the architecture, activities, algorithms and probability of success in breaking authentication.

Keywords: cloud computing, cloud security, integrity, multi-tenancy, security

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Authors: Hesam Khajehsaeid, Naeimeh Alagheband

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Magnetorheological fluids (MRF) are a category of smart materials. They exhibit a reversible change from a Newtonian-like fluid to a semi-solid state upon application of an external magnetic field. In contrast to ordinary fluids, MRFs can tolerate shear stresses up to a threshold value called yield stress which strongly depends on the strength of the magnetic field, magnetic particles volume fraction and temperature. Even beyond the yield, a magnetic field can increase MR fluid viscosity up to several orders. As yield stress is an important parameter in the design of MR devices, in this work, the effects of magnetic field intensity and magnetic particle concentration on the yield stress of MRFs are investigated. Four MRF samples with different particle concentrations are developed and tested through flow-ramp analysis to obtain the flow curves at a range of magnetic field intensity as well as shear rate. The viscosity of the fluids is determined by means of the flow curves. The results are then used to determine the yield stresses by means of the steady stress sweep method. The yield stresses are then determined by means of a modified form of the dipole model as well as empirical models. The exponential distribution function is used to describe the orientation of particle chains in the dipole model under the action of the external magnetic field. Moreover, the modified dipole model results in a reasonable distribution of chains compared to previous similar models.

Keywords: magnetorheological fluids, yield stress, particles concentration, dipole model

Procedia PDF Downloads 179

Authors: F. R. M. Nascimento, E. E. S. Lora, J. C. E. Palácio

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A mathematical model to investigate the performance of a two stage fixed bed downdraft gasifier operating with air, steam and oxygen mixtures as the gasifying fluid has been developed. The various conditions of mixtures for a double stage fluid entry, have been performed. The model has been validated through a series of experimental tests performed by NEST – The Excellence Group in Thermal and Distributed Generation of the Federal University of Itajubá. Influence of mixtures are analyzed through the Steam to Biomass (SB), Equivalence Ratio (ER) and the Oxygen Concentration (OP) parameters in order to predict the best operating conditions to obtain adequate output gas quality, once is a key parameter for subsequent gas processing in the synthesis of biofuels, heat and electricity generation. Results show that there is an optimal combination in the steam and oxygen content of the gasifying fluid which allows the user find the best conditions to design and operate the equipment according to the desired application.

Keywords: air, equilibrium, downdraft, fixed bed gasification, mathematical modeling, mixtures, oxygen steam

Procedia PDF Downloads 481

Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Assigning aircrafts’ activities to appropriate gates is one the most challenging issues in airport authorities’ multiple criteria decision making. The potential financial loss due to imbalances of demand and supply in congested airports, higher occupation rates of gates, and the existing restrictions to expand facilities provide further evidence for the need for an optimal supply allocation. Passengers walking distance, towing movements, extra fuel consumption (as a result of awaiting longer to taxi when taxi conflicts happen at the apron area), etc. are the major traditional components involved in GAP models. In particular, the total cost associated with gate assignment problem highly depends on the airport terminal layout. The study herein presents a well-elaborated literature review on the topic focusing on major concerns, applicable variables and objectives, as well as proposing a three-objective mathematical model for the gate assignment problem. The model has been tested under different concourse layouts in order to check its performance in different scenarios. Results revealed that terminal layout pattern is a significant parameter in airport and that the proposed model is capable of dealing with key constraints and objectives, which supports its practical usability for future decision making tools. Potential solution techniques were also suggested in this study for future works.

Keywords: airport management, terminal layout, gate assignment problem, mathematical modeling

Procedia PDF Downloads 230

Authors: Ella Sèdé Maforikan

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Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

Procedia PDF Downloads 309

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Rahman Mofidi, Sina Rahimi, Farnoosh Darban

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Communication plays a key role in today’s world, and to support it, the quality of service has the highest priority. It is very important to differentiate between traffic based on priority level. Some traffic classes should be a higher priority than other classes. It is also necessary to give high priority to customers who have more payment for better service, however, without influence on other customers. So to realize that, we will require effective quality of service methods. To ensure the optimal performance of the network in accordance with the quality of service is an important goal for all operators in the mobile network. In this work, we propose an algorithm based on control parameters which it’s based on user feedback that aims at minimizing the access to system transmit power and thus improving the network key performance indicators and increasing the quality of service. This feedback that is known as channel quality indicator (CQI) indicates the received signal level of the user. We aim at proposing an algorithm in control parameter criterion to study improving the quality of service and throughput in a cellular network at the simulated environment. In this work we tried to parameter values have close to their actual level. Simulation results show that the proposed algorithm improves the system throughput and thus satisfies users' throughput and improves service to set up a successful call.

Keywords: quality of service, key performance indicators, control parameter, channel quality indicator

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Authors: Madhu Aneja, Sapna Sharma

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The water-based bioconvection of a nanofluid containing motile gyrotactic micro-organisms over nonlinear inclined stretching sheet has been investigated. The governing nonlinear boundary layer equations of the model are reduced to a system of ordinary differential equations via Oberbeck-Boussinesq approximation and similarity transformations. Further, the modified set of equations with associated boundary conditions are solved using Finite Element Method. The impact of various pertinent parameters on the velocity, temperature, nanoparticles concentration, density of motile micro-organisms profiles are obtained and analyzed in details. The results show that with the increase in angle of inclination δ, velocity decreases while temperature, nanoparticles concentration, a density of motile micro-organisms increases. Additionally, the skin friction coefficient, Nusselt number, Sherwood number, density number are computed for various thermophysical parameters. It is noticed that increasing Brownian motion and thermophoresis parameter leads to an increase in temperature of fluid which results in a reduction in Nusselt number. On the contrary, Sherwood number rises with an increase in Brownian motion and thermophoresis parameter. The findings have been validated by comparing the results of special cases with existing studies.

Keywords: bioconvection, finite element method, gyrotactic micro-organisms, inclined stretching sheet, nanofluid

Procedia PDF Downloads 189

Authors: Z. Hormozi Moghaddam, M. Mokhtari-Dizaji, M. Movahedin, M. E. Ravari

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Mechanical index (MI) is used for quantifying acoustic cavitation and the relationship between acoustic pressure and the frequency. In this study, modeling of the MI was applied to provide treatment protocol and to understand the effective physical processes on reproducibility of stem cells. The acoustic pressure and MI equations are modeled and solved to estimate optimal MI for 28, 40, 150 kHz and 1 MHz frequencies. Radial and axial acoustic pressure distribution was extracted. To validate the results of the modeling, the acoustic pressure in the water and near field depth was measured by a piston hydrophone. Results of modeling and experiments show that the model is consistent well to experimental results with 0.91 and 0.90 correlation of coefficient (p<0.05) for 1 MHz and 40 kHz. Low intensity ultrasound with 0.40 MI is more effective on the proliferation rate of the spermatogonial stem cells during the seven days of culture, in contrast, high MI has a harmful effect on the spermatogonial stem cells. This model provides proper treatment planning in vitro and in vivo by estimating the cavitation phenomenon.

Keywords: ultrasound, mechanical index, modeling, stem cell

Procedia PDF Downloads 334

Authors: Joseph C. Chen, Venkata Karthik Jakka

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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: injection molding processes, taguchi parameter design, tensile strength, high-density polyethylene(HDPE)

Procedia PDF Downloads 196

Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

Abstract:

System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

Abstract:

This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

Procedia PDF Downloads 143

Authors: A. Khodabakhshi, A. Mortazavi

Abstract:

Accurate determination of rock mass deformation modulus, as an important design parameter, is one of the most controversial issues in most engineering projects. A 3D numerical model of standard plate load test (PLT) using the FLAC3D code was carried to investigate the mechanism governing the test process. Five objectives were the focus of this study. The first goal was to employ 3D modeling in the interpretation of PLT conducted at the Bazoft dam site, Iran. The second objective was to investigate the effect of displacements measuring depth from the loading plates on the calculated moduli. The magnitude of rock mass deformation modulus calculated from PLT depends on anchor depth, and in practice, this may be a cause of error in the selection of realistic deformation modulus for the rock mass. The third goal of the study was to investigate the effect of testing plate diameter on the calculated modulus. Moreover, a comparison of the calculated modulus from ISRM formula, numerical modeling and calculated modulus from the actual PLT carried out at right abutment of the Bazoft dam site was another objective of the study. Finally, the effect of plastic strains on the calculated moduli in each of the loading-unloading cycles for three loading plates was investigated. The geometry, material properties, and boundary conditions on the constructed 3D model were selected based on the in-situ conditions of PLT at Bazoft dam site. A good agreement was achieved between numerical model results and the field tests results.

Keywords: deformation modulus, numerical model, plate loading test, rock mass

Procedia PDF Downloads 170

Authors: Ceren Vardar Acar, Mine Caglar

Abstract:

In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

Procedia PDF Downloads 483