Search results for: planetary model of the atom

Authors: Anthony Usoro

Abstract:

In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Mauludi Ariesto Pamungkas, Wafa Maftuhin

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Gallium with three outer electrons commonly are used as dopants of silicon to make it P type and N type semiconductor respectively. Silicene, one-atom-thick silicon layer is one of emerging two dimension materials after the success of graphene. The effects of Gallium doping on electronic structure of silicine are investigated by using first principle calculation based on Density Functional Theory (DFT) calculation and norm conserving pseudopotential method implemented in ABINIT code. Bandstructure of Pristine silicene is similar to that of graphene. Effect of Ga doping on bandstructure of silicene depend on the position of Ga adatom on silicene

Keywords: silicene, effects of Gallium doping, Density Functional Theory (DFT), graphene

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Authors: Khodzhaberdi Allaberdiev

Abstract:

Aromaticity, one of the most important concepts in organic chemistry, has attracted considerable interest from both experimentalists and theoreticians. The geometry optimization of p-substituted o-(N-dialkyl)aminomethylphenols, o-DEAMPH XC₆ H₅CH ₂Y (X=p-OCH₃, CH₃, H, F, Cl, Br, COCH₃, COOCH₃, CHO, CN and NO₂, Y=o-N (C₂H₅)₂, o-DEAMPHs have been performed in the gas phase using the B3LYP/6-311+G(d,p) level. Aromaticities of the considered molecules were investigated using different indices included geometrical (HOMA and Bird), electronic (FLU, PDI and SA) magnetic (NICS(0), NICS(1) and NICS(1)zz indices. The linear dependencies were obtained between some aromaticity indices. The best correlation is observed between the Bird and PDI indices (R² =0.9240). However, not all types of indices or even different indices within the same type correlate well among each other. Surprisingly, for studied molecules in which geometrical and electronic cannot correctly give the aromaticity of ring, the magnetism based index successfully predicts the aromaticity of systems. 1H NMR spectra of compounds were obtained at B3LYP/6–311+G(d,p) level using the GIAO method. Excellent linear correlation (R²= 0.9996) between values the chemical shift of hydrogen atom obtained experimentally of 1H NMR and calculated using B3LYP/6–311+G(d,p) demonstrates a good assignment of the experimental values chemical shift to the calculated structures of o-DEAMPH. It is found that the best linear correlation with the Hammett substituent constants is observed for the NICS(1)zz index in comparison with the other indices: NICS(1)zz =-21.5552+1,1070 σp- (R²=0.9394). The presence intramolecular hydrogen bond in the studied molecules also revealed changes the aromatic character of substituted o-DEAMPHs. The HOMA index predicted for R=NO2 the reduction in the π-electron delocalization of 3.4% was about double that observed for p-nitrophenol. The influence intramolecular H-bonding on aromaticity of benzene ring in the ground state (S0) are described by equations between NICS(1)zz and H-bond energies: experimental, Eₑₓₚ, predicted IR spectroscopical, Eν and topological, EQTAIM with correlation coefficients R² =0.9666, R² =0.9028 and R² =0.8864, respectively. The NICS(1)zz index also correlates with usual descriptors of the hydrogen bond, while the other indices do not give any meaningful results. The influence of the intramolecular H-bonding formation on the aromaticity of some substituted o-DEAMPHs is criteria to consider the multidimensional character of aromaticity. The linear relationships as well as revealed between NICS(1)zz and both pyramidality nitrogen atom, ΣN(C₂H₅)₂ and dihedral angle, φ CAr – CAr -CCH₂ –N, to characterizing out-of-plane properties.These results demonstrated the nonplanar structure of o-DEAMPHs. Finally, when considering dependencies of NICS(1)zz, were excluded data for R=H, because the NICS(1) and NICS(1)zz values are the most negative for unsubstituted DEAMPH, indicating its highest aromaticity; that was not the case for NICS(0) index.

Keywords: aminomethylphenols, DFT, aromaticity, correlations

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Authors: Shank Kulkarni, Alireza Tabarraei

Abstract:

The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

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Authors: Hussein Altartouri

Abstract:

In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: Ioan Rusu

Abstract:

Let us consider that the entire universe is composed of a single hydrogen atom within which the electron is moving around the proton. In this case, according to classical theories of physics, radiation and photons, respectively, should be absorbed by the electron. Depending on the number of photons absorbed, the electron radius of rotation around the proton is established. Until now, the principle of photon absorption by electrons and the electron transition to a new energy level, namely to a higher radius of rotation around the proton, is not clarified in physics. This paper aims to demonstrate that photons have mass and negative electrostatic charge similar to electrons but infinitely smaller. The experiments which demonstrate this theory are simple: thermal expansion, photoelectric effect and thermonuclear reaction.

Keywords: electrostatic, electron, photon, proton, radiation

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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Authors: Anna Avramenko, Heikki Haario

Abstract:

This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Jui-Ching Chou

Abstract:

Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.

Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

Abstract:

This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Amani Tahat, Serdal Kirmizialtin

Abstract:

Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

Abstract:

In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Rabah Haoui

Abstract:

Hypersonic flows around spatial vehicles during their reentry phase in planetary atmospheres are characterized by intense aerothermodynamics phenomena. The aim of this work is to analyze high temperature flows around an axisymmetric blunt body taking into account chemical and vibrational non-equilibrium for air mixture species and the no slip condition at the wall. For this purpose, the Navier-Stokes equations system is resolved by the finite volume methodology to determine the flow parameters around the axisymmetric blunt body especially at the stagnation point and in the boundary layer along the wall of the blunt body. The code allows the capture of shock wave before a blunt body placed in hypersonic free stream. The numerical technique uses the Flux Vector Splitting method of Van Leer. CFL coefficient and mesh size level are selected to ensure the numerical convergence.

Keywords: hypersonic flow, viscous flow, chemical kinetic, dissociation, finite volumes, frozen and non-equilibrium flow

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: Nikhil Agrawal, Adam A. Skelton

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Alzheimer’s disease (AD) is one of the most common forms of dementia, which is caused by misfolding and aggregation of amyloid beta (Aβ) peptides into amyloid-β fibrils (Aβ fibrils). To disrupt the remodeling of Aβ fibrils, a number of candidate molecules have been proposed. To study the molecular mechanisms of Aβ fibrils remodeling we performed a series of all-atom molecular dynamics simulations, a total time of 3µs, in explicit solvent. Several previously undiscovered candidate molecule-Aβ fibrils binding modes are unraveled; one of which shows the direct conformational change of the Aβ fibril by understanding the physicochemical factors responsible for binding and subsequent remodeling of Aβ fibrils by the candidate molecule, open avenues into structure-based drug design for AD can be opened.

Keywords: alzheimer’s disease, amyloid, MD simulations, misfolded protein

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Authors: Gabriela D. Silva, Rodrigo L. O. R. Cunha, Mauricio D. Coutinho-Neto

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In the last four decades the biological activities of selenium compounds has received great attention, particularly for hypervalent derivates from selenium (IV) used as enzyme inhibitors. The unregulated activity of cysteine proteases are related to the development of several pathologies, such as neurological disorders, cardiovascular diseases, obesity, rheumatoid arthritis, cancer and parasitic infections. These enzymes are therefore a valuable target for designing new small molecule inhibitors such as selenuranes. Even tough there has been advances in the synthesis and design of new selenuranes based inhibitors, little is known about their mechanism of action. It is a given that inhibition occurs through the reaction between the thiol group of the enzyme and the chalcogen atom. However, several open questions remain about the nature of the mechanism (associative vs. dissociative) and about the nature of the reactive species in solution under physiological conditions. In this work we performed a theoretical investigation on model systems to study the possible routes of substitution reactions. Nucleophiles may be present in biological systems, our interest is centered in the thiol groups from the cysteine proteases and the hydroxyls from the aqueous environment. We therefore expect this study to clarify the possibility of a route reaction in two stages, the first consisting of the substitution of chloro atoms by hydroxyl groups and then replacing these hydroxyl groups per thiol groups in selenuranes. The structures of selenuranes and nucleophiles were optimized using density function theory along the B3LYP functional and a 6-311+G(d) basis set. Solvent was treated using the IEFPCM method as implemented in the Gaussian 09 code. Our results indicate that hydrolysis from water react preferably with selenuranes, and then, they are replaced by the thiol group. It show the energy values of -106,0730423 kcal/mol for dople substituition by hydroxyl group and 96,63078511 kcal/mol for thiol group. The solvatation and pH reduction promotes this route, increasing the energy value for reaction with hydroxil group to -50,75637672 kcal/mol and decreasing the energy value for thiol to 7,917767189 kcal/mol. Alternative ways were analyzed for monosubstitution (considering the competition between Cl, OH and SH groups) and they suggest the same route. Similar results were obtained for aliphatic and aromatic selenuranes studied.

Keywords: chalcogenes, computational study, cysteine proteases, enzyme inhibitors

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

Abstract:

In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Coskun Serefoglu

Abstract:

The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Emre Ünal, Hasan Başaran

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In this study, starting with a predetermined Lunar free-return trajectory, an analysis of major near-Earth perturbations is carried out. Referencing to historical Apollo-13 flight, changes in the mission’s resultant perimoon and perigee altitudes with each perturbative effect are evaluated. The perturbations that were considered are Earth oblateness effects, up to the 6^th order, atmospheric drag, third body perturbations consisting of solar and planetary effects and solar radiation pressure effects. It is found that for a Moon mission, most of the main perturbative effects spoil the trajectory significantly while some came out to be negligible. It is seen that for apparent future request of constructing low cost, reliable and safe trajectories to the Moon, most of the orbital perturbations are crucial.

Keywords: Apollo-13 trajectory, atmospheric drag, lunar trajectories, oblateness effect, perturbative effects, solar radiation pressure, third body perturbations

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Authors: Laura Kocsor, Laszlo Peter, Laszlo Kovacs, Zsolt Kis

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The aim of our research is to prepare rare-earth-doped lithium niobate (LiNbO3) nanocrystals, having only a few dopant ions in the focal point of an exciting laser beam. These samples will be used to achieve individual addressing of the dopant ions by light beams in a confocal microscope setup. One method for the preparation of nanocrystalline materials is to reduce the particle size by mechanical grinding. High-energy ball-milling was used in several works to produce nano lithium niobate. Previously, it was reported that dry high-energy ball-milling of lithium niobate in a shaker mill results in the partial reduction of the material, which leads to a balanced formation of bipolarons and polarons yielding gray color together with oxygen release and Li2O segregation on the open surfaces. In the present work we focus on preparing LiNbO3 nanocrystals by high-energy ball-milling using a Fritsch Pulverisette 7 planetary mill. Every ball-milling process was carried out in zirconia vial with zirconia balls of different sizes (from 3 mm to 0.1 mm), wet grinding with water, and the grinding time being less than an hour. Gradually decreasing the ball size to 0.1 mm, an average particle size of about 10 nm could be obtained determined by dynamic light scattering and verified by scanning electron microscopy. High-energy ball-milling resulted in sample darkening evidenced by optical absorption spectroscopy measurements indicating that the material underwent partial reduction. The unwanted lithium oxide loss decreases the Li/Nb ratio in the crystal, strongly influencing the spectroscopic properties of lithium niobate. Zirconia contamination was found in ground samples proved by energy-dispersive X-ray spectroscopy measurements; however, it cannot be explained based on the hardness properties of the materials involved in the ball-milling process. It can be understood taking into account the presence of lithium hydroxide formed the segregated lithium oxide and water during the ball-milling process, through chemically induced abrasion. The quantity of the segregated Li2O was measured by coulometric titration. During the wet milling process in the planetary mill, it was found that the lithium oxide loss increases linearly in the early phase of the milling process, then a saturation of the Li2O loss can be seen. This change goes along with the disappearance of the relatively large particles until a relatively narrow size distribution is achieved in accord with the dynamic light scattering measurements. With the 3 mm ball size and 1100 rpm rotation rate, the mean particle size achieved is 100 nm, and the total Li2O loss is about 1.2 wt.% of the original LiNbO3. Further investigations have been done to minimize the Li2O segregation during the ball-milling process. Since the Li2O loss was observed to increase with the growing total surface of the particles, the influence of ball-milling parameters on its quantity has also been studied.

Keywords: high-energy ball-milling, lithium niobate, mechanochemical reaction, nanocrystals

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

Abstract:

Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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