Abstract: Percentage of soil-gas radon-222 concentration (222Rn) from soil-depths contributing to outdoor radon atmospheric level depends largely on some physical parameters of the soil. To determine its dependency in soil-depths, survey tests were carried out on soil depths and grain size particles using in-situ measurement method of soil-gas radon-222 concentration at different soil depths. The measurements were carried out with an electronic active radon detector (RAD-7) manufactured by Durridge Company USA. Radon-222 concentrations (222Rn) in soil-gas were measured at four different soil depths of 20, 40, 60 and 100 cm in five feasible locations. At each soil depth, soil samples were collected for grain size particle analysis using soil grasp sampler. The result showed that highest value of radon-222 concentration (24,680 ± 1960 Bqm-3) was measured at 100 cm depth with utmost grain size particle of 17.64% while the lowest concentration (7370 ± 1139 Bqm-3) was measured at 100 cm depth with least grain size particle of 10.75% respectively. A computational model was derived using SPSS regression package. This model could be a yardstick for prediction on soil gas radon concentration reference to soil grain size particle at different soil-depths.
Abstract: In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.
Abstract: In a nuclear reactor, an array of fuel rods containing stacked uranium dioxide pellets clad with zircalloy is the heat source for a thermodynamic cycle of energy conversion from heat to electricity. After fuel is used in a nuclear reactor, the assemblies are stored underwater in a spent nuclear fuel pool at the nuclear power plant while heat generation and radioactive decay rates decrease before it is placed in packages for dry storage or transportation. A computational model of a Boiling Water Reactor spent fuel assembly is modeled using FLUENT, the computational fluid dynamics package. Heat transfer simulations were performed on the two-dimensional 9x9 spent fuel assembly to predict the maximum cladding temperature for different input to the FLUENT model. Uncertainty quantification is used to predict the heat transfer and the maximum temperature profile inside the assembly.
Abstract: Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.
Abstract: The main purpose of this study is to show differences between the numerical solution of the flow through the artificial heart valve using Newtonian or non-Newtonian fluid. The simulation was carried out by a commercial computational fluid dynamics (CFD) package based on finite-volume method. An aortic bileaflet heart valve (Sorin Bicarbon) was used as a pattern for model of real heart valve replacement. Computed tomography (CT) was used to gain the accurate parameters of the valve. Data from CT were transferred in the commercial 3D designer, where the model for CFD was made. Carreau rheology model was applied as non-Newtonian fluid. Physiological data of cardiac cycle were used as boundary conditions. Outputs were taken the leaflets excursion from opening to closure and the fluid dynamics through the valve. This study also includes experimental measurement of pressure fields in ambience of valve for verification numerical outputs. Results put in evidence a favorable comparison between the computational solutions of flow through the mechanical heart valve using Newtonian and non-Newtonian fluid.
Abstract: Head injury in childhood is a common cause of death or permanent disability from injury. However, despite its frequency and significance, there is little understanding of how a child’s head responds during injurious loading. Whilst Infant Post Mortem Human Subject (PMHS) experimentation is a logical approach to understand injury biomechanics, it is the authors’ opinion that a lack of subject availability is hindering potential progress. Computer modelling adds great value when considering adult populations; however, its potential remains largely untapped for infant surrogates. The complexities of child growth and development, which result in age dependent changes in anatomy, geometry and physical response characteristics, present new challenges for computational simulation. Further geometric challenges are presented by the intricate infant cranial bones, which are separated by sutures and fontanelles and demonstrate a visible fibre orientation. This study presents an FE model of a newborn infant’s head, developed from high-resolution computer tomography scans, informed by published tissue material properties. To mimic the fibre orientation of immature cranial bone, anisotropic properties were applied to the FE cranial bone model, with elastic moduli representing the bone response both parallel and perpendicular to the fibre orientation. Biofiedility of the computational model was confirmed by global validation against published PMHS data, by replicating experimental impact tests with a series of computational simulations, in terms of head kinematic responses. Numerical results confirm that the FE head model’s mechanical response is in favourable agreement with the PMHS drop test results.
Abstract: We assume that conscious functions are implemented
automatically. In other words that consciousness as well as the
non-consciousness aspect of human thought, planning and perception,
are produced by biologically adaptive algorithms. We propose that
the mechanisms of consciousness can be produced using similar
adaptive algorithms to those executed by the mechanism. In this
paper, we present a computational model of consciousness, the
”Global Abstraction Workspace” which is an internal environmental
modelling perceived as a multi-agent system. This system is able to
evolve and generate new data and processes as well as actions in the
environment.
Abstract: Lateral Geniculate Nucleus (LGN) is the relay center
in the visual pathway as it receives most of the input information
from retinal ganglion cells (RGC) and sends to visual cortex. Low
threshold calcium currents (IT) at the membrane are the unique
indicator to characterize this firing functionality of the LGN neurons
gained by the RGC input. According to the LGN functional
requirements such as functional mapping of RGC to LGN, the
morphologies of the LGN neurons were developed. During the
neurological disorders like glaucoma, the mapping between RGC and
LGN is disconnected and hence stimulating LGN electrically using
deep brain electrodes can restore the functionalities of LGN. A
computational model was developed for simulating the LGN neurons
with three predominant morphologies each representing different
functional mapping of RGC to LGN. The firings of action potentials
at LGN neuron due to IT were characterized by varying the
stimulation parameters, morphological parameters and orientation. A
wide range of stimulation parameters (stimulus amplitude, duration
and frequency) represents the various strengths of the electrical
stimulation with different morphological parameters (soma size,
dendrites size and structure). The orientation (0-1800) of LGN
neuron with respect to the stimulating electrode represents the angle
at which the extracellular deep brain stimulation towards LGN
neuron is performed. A reduced dendrite structure was used in the
model using Bush–Sejnowski algorithm to decrease the
computational time while conserving its input resistance and total
surface area. The major finding is that an input potential of 0.4 V is
required to produce the action potential in the LGN neuron which is
placed at 100 μm distance from the electrode. From this study, it can
be concluded that the neuroprostheses under design would need to
consider the capability of inducing at least 0.4V to produce action
potentials in LGN.
Abstract: The quantitative study of cell mechanics is of
paramount interest, since it regulates the behaviour of the living cells
in response to the myriad of extracellular and intracellular
mechanical stimuli. The novel experimental techniques together with
robust computational approaches have given rise to new theories and
models, which describe cell mechanics as combination of
biomechanical and biochemical processes. This review paper
encapsulates the existing continuum-based computational approaches
that have been developed for interpreting the mechanical responses of
living cells under different loading and boundary conditions. The
salient features and drawbacks of each model are discussed from both
structural and biological points of view. This discussion can
contribute to the development of even more precise and realistic
computational models of cell mechanics based on continuum
approaches or on their combination with microstructural approaches,
which in turn may provide a better understanding of
mechanotransduction in living cells.
Abstract: The modeling lung respiratory system that has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the pulmonary lung system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically relevant three-dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue that produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue viscoelasticity and tidal breathing period.
Abstract: A mathematical model of the additional effects of the
liquid in the hydrodynamic gap is presented in the paper. An
incompressible viscous fluid is considered. Based on computational
modeling are determined the matrices of mass, stiffness and damping.
The mathematical model is experimentally verified.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: Two finite element (FEM) models are presented in
this paper to address the random nature of the response of glued
timber structures made of wood segments with variable elastic
moduli evaluated from 3600 indentation measurements. This total
database served to create the same number of ensembles as was the
number of segments in the tested beam. Statistics of these ensembles
were then assigned to given segments of beams and the Latin
Hypercube Sampling (LHS) method was called to perform 100
simulations resulting into the ensemble of 100 deflections subjected
to statistical evaluation. Here, a detailed geometrical arrangement of
individual segments in the laminated beam was considered in the
construction of two-dimensional FEM model subjected to in fourpoint
bending to comply with the laboratory tests. Since laboratory
measurements of local elastic moduli may in general suffer from a
significant experimental error, it appears advantageous to exploit the
full scale measurements of timber beams, i.e. deflections, to improve
their prior distributions with the help of the Bayesian statistical
method. This, however, requires an efficient computational model
when simulating the laboratory tests numerically. To this end, a
simplified model based on Mindlin’s beam theory was established.
The improved posterior distributions show that the most significant
change of the Young’s modulus distribution takes place in laminae in
the most strained zones, i.e. in the top and bottom layers within the
beam center region. Posterior distributions of moduli of elasticity
were subsequently utilized in the 2D FEM model and compared with
the original simulations.
Abstract: Nanoscale thermites such as the composite mixture of
nano-sized aluminum and molybdenum trioxide powders possess
several technical advantages such as much higher reaction rate and
shorter ignition delay, when compared to the conventional energetic
formulations made of micron-sized metal and oxidizer particles. In this
study, the self-propagation of combustion wave in compacted pellets
of nanoscale thermite composites is modeled and computationally
investigated by utilizing the activation energy reduction of aluminum
particles due to nanoscale particle sizes. The present computational
model predicts the speed of combustion wave propagation which is
good agreement with the corresponding experiments of thermite
reaction. Also, several characteristics of thermite reaction in nanoscale
composites are discussed including the ignition delay and combustion
wave structures.
Abstract: The typical insects employ a flapping-wing mode of flight. The numerical simulations on free flight of a model fruit fly (Re=143) including hovering and are presented in this paper. Unsteady aerodynamics around a flapping insect is studied by solving the three-dimensional Newtonian dynamics of the flyer coupled with Navier-Stokes equations. A hybrid-grid scheme (Generalized Finite Difference Method) that combines great geometry flexibility and accuracy of moving boundary definition is employed for obtaining flow dynamics. The results show good points of agreement and consistency with the outcomes and analyses of other researchers, which validate the computational model and demonstrate the feasibility of this computational approach on analyzing fluid phenomena in insect flight. The present modeling approach also offers a promising route of investigation that could complement as well as overcome some of the limitations of physical experiments in the study of free flight aerodynamics of insects. The results are potentially useful for the design of biomimetic flapping-wing flyers.
Abstract: Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.
Abstract: Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.
Abstract: Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.
Abstract: Coupled shear walls consist of two shear walls connected intermittently by beams along the height. The behavior of coupled shear walls is mainly governed by the coupling beams. The coupling beams are designed for ductile inelastic behavior in order to dissipate energy. The base of the shear walls may be designed for elastic or ductile inelastic behavior. The amount of energy dissipation depends on the yield moment capacity and plastic rotation capacity of the coupling beams. In this paper, an analytical model of coupling beam was developed to calculate the rotations and moment capacities of coupling beam with conventional reinforcement.
Abstract: The objective of this paper is to develop a computational model of human nasal cavity from computed tomography (CT) scans using MIMICS software. Computational fluid dynamic techniques were employed to understand nasal airflow. Gambit and Fluent software was used to perform CFD simulation. Velocity profiles, iteration plots, pressure distribution, streamline and pathline patterns for steady, laminar airflow inside the human nasal cavity of healthy and also infected persons are presented in detail. The implications for olfaction are visualized. Results are validated with the available numerical and experimental data. The graphs reveal that airflow varies with different anatomical nasal structures and only fraction of the inspired air reaches the olfactory region. The Deviations in the results suggest that the treatment of infected volunteers will improve the olfactory function.