Search results for: neuron mechanics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 525

Search results for: neuron mechanics

405 From Wave-Powered Propulsion to Flight with Membrane Wings: Insights Powered by High-Fidelity Immersed Boundary Methods based FSI Simulations

Authors: Rajat Mittal, Jung Hee Seo, Jacob Turner, Harshal Raut

Abstract:

The perpetual advancement in computational capabilities, coupled with the continuous evolution of software tools and numerical algorithms, is creating novel avenues for research, exploration, and application at the nexus of computational fluid and structural mechanics. Fish leverage their remarkably flexible bodies and fins to harness energy from vortices, propelling themselves with an elegance and efficiency that captivates engineers. Bats fly with unparalleled agility and speed by using their flexible membrane wings. Wave-assisted propulsion (WAP) systems, utilizing elastically mounted hydrofoils, convert wave energy into thrust. Each of these problems involves a complex and elegant interplay between fluid dynamics and structural mechanics. Historically, investigations into such phenomena were constrained by available tools, but modern computational advancements now facilitate exploration of these multi-physics challenges with an unprecedented level of fidelity, precision, and realism. In this work, the author will discuss projects that harness the capabilities of high-fidelity sharp-interface immersed boundary methods to address a spectrum of engineering and biological challenges involving fluid-structure interaction.

Keywords: immersed boundary methods, CFD, bioflight, fluid structure interaction

Procedia PDF Downloads 49
404 Explosion Mechanics of Aluminum Plates Subjected to the Combined Effect of Blast Wave and Fragment Impact Loading: A Multicase Computational Modeling Study

Authors: Atoui Oussama, Maazoun Azer, Belkassem Bachir, Pyl Lincy, Lecompte David

Abstract:

For many decades, researchers have been focused on understanding the dynamic behavior of different structures and materials subjected to fragment impact or blast loads separately. The explosion mechanics, as well as the impact physics studies dealing with the numerical modeling of the response of protective structures under the synergistic effect of a blast wave and the impact of fragments, are quite limited in the literature. This article numerically evaluates the nonlinear dynamic behavior and damage mechanisms of Aluminum plates EN AW-1050A- H24 under different combined loading scenarios varied by the sequence of the applied loads using the commercial software LS-DYNA. For one hand, with respect to the terminal ballistic field investigations, a Lagrangian (LAG) formulation is used to evaluate the different failure modes of the target material in case of a fragment impact. On the other hand, with respect to the blast field analysis, an Arbitrary Lagrangian-Eulerian (ALE) formulation is considered to study the fluid-structure interaction (FSI) of the shock wave and the plate in case of a blast loading. Four different loading scenarios are considered: (1) only blast loading, (2) only fragment impact, (3) blast loading followed by a fragment impact and (4) a fragment impact followed by blast loading. From the numerical results, it was observed that when the impact load is applied to the plate prior to the blast load, it suffers more severe damage due to the hole enlargement phenomenon and the effects of crack propagation on the circumference of the damaged zone. Moreover, it was found that the hole from the fragment impact loading was enlarged to about three times in diameter as compared to the diameter of the projectile. The validation of the proposed computational model is based in part on previous experimental data obtained by the authors and in the other part on experimental data obtained from the literature. A good correspondence between the numerical and experimental results is found.

Keywords: computational analysis, combined loading, explosion mechanics, hole enlargement phenomenon, impact physics, synergistic effect, terminal ballistic

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403 A Finite Element Based Predictive Stone Lofting Simulation Methodology for Automotive Vehicles

Authors: Gaurav Bisht, Rahul Rathnakumar, Ravikumar Duggirala

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Predictive simulations are one of the key focus areas in safety-critical industries such as aerospace and high-performance automotive engineering. The stone-chipping study is one such effort taken up by the industry to predict and evaluate the damage caused due to gravel impact on vehicles. This paper describes a finite elements based method that can simulate the ejection of gravel chips from a vehicle tire. The FE simulations were used to obtain the initial ejection velocity of the stones for various driving conditions using a computational contact mechanics approach. To verify the accuracy of the tire model, several parametric studies were conducted. The FE simulations resulted in stone loft velocities ranging from 0–8 m/s, regardless of tire speed. The stress on the tire at the instant of initial contact with the stone increased linearly with vehicle speed. Mesh convergence studies indicated that a highly resolved tire mesh tends to result in better momentum transfer between the tire and the stone. A fine tire mesh also showed a linearly increasing relationship between the tire forward speed and stone lofting speed, which was not observed in coarser meshes. However, it also highlighted a potential challenge, in that the ejection velocity vector of the stone seemed to be sensitive to the mesh, owing to the FE-based contact mechanical formulation of the problem.

Keywords: abaqus, contact mechanics, foreign object debris, stone chipping

Procedia PDF Downloads 255
402 Brain-Derived Neurotrophic Factor and It's Precursor ProBDNF Serum Levels in Adolescents with Mood Disorders: 2-Year Follow-Up Study

Authors: M. Skibinska, A. Rajewska-Rager, M. Dmitrzak-Weglarz, N. Lepczynska, P. Sibilski, P. Kapelski, J. Pawlak, J. Twarowska-Hauser

Abstract:

Introduction: Neurotrophic factors have been implicated in neuropsychiatric disorders. Brain-Derived Neurotrophic Factor (BDNF) influences neuron differentiation in development as well as synaptic plasticity and neuron survival in adulthood. BDNF is widely studied in mood disorders and has been proposed as a biomarker for depression. BDNF is synthesized as precursor protein – proBDNF. Both forms are biologically active and exert opposite effects on neurons. Aim: The aim of the study was to examine the serum levels of BDNF and proBDNF in unipolar and bipolar young patients below 24 years old during hypo/manic, depressive episodes and in remission compared to healthy control group. Methods: In a prospective 2 years follow-up study, we investigated alterations in levels of BDNF and proBDNF in 79 patients (23 males, mean age 19.08, SD 3.3 and 56 females, mean age 18.39, SD 3.28) diagnosed with mood disorders: unipolar and bipolar disorder compared with 35 healthy control subjects (7 males, mean age 20.43, SD 4.23 and 28 females, mean age 21.25, SD 2.11). Clinical characteristics including mood, comorbidity, family history, and treatment, were evaluated during control visits and clinical symptoms were rated using the Hamilton Depression Rating Scale and Young Mania Rating Scale. Serum BDNF and proBDNF concentrations were determined by Enzyme-Linked Immunosorbent Assays (ELISA) method. Serum BDNF and proBDNF levels were analysed with covariates: sex, age, age > 18 and < 18 years old, family history of affective disorders, drug-free vs. medicated status. Normality of the data was tested using Shapiro-Wilk test. Levene’s test was used to calculate homogeneity of variance. Non-parametric Tests: Mann-Whitney U test, Kruskal-Wallis ANOVA, Friedman’s ANOVA, Wilcoxon signed rank test, Spearman correlation coefficient were applied in analyses The statistical significance level was set at p < 0.05. Results: BDNF and proBDNF serum levels did not differ between patients at baseline and controls as well as comparing patients in acute episode of depression/hypo/mania at baseline and euthymia (at month 3 or 6). Comparing BDNF and proBDNF levels between patients in euthymia and control group no differences have been found. Increased BDNF level in women compared to men at baseline (p=0.01) have been observed. BDNF level at baseline was negatively correlated with depression and mania occurence at 24 month (p=0.04). BDNF level at 12 month was negatively correlated with depression and mania occurence at 12 month (p=0.01). Correlation of BDNF level with sex have been detected (p=0.01). proBDNF levels at month 3, 6 and 12 negatively correlated with disease status (p=0.02, p=0.008, p=0.009, respectively). No other correlations of BDNF and proBDNF levels with clinical and demographical variables have been detected. Discussion: Our results did not show any differences in BDNF and proBDNF levels between depression, mania, euthymia, and controls. Imbalance in BDNF/proBDNF signalling may be involved in pathogenesis of mood disorders. Further studies on larger groups are recommended. Grant was founded by National Science Center in Poland no 2011/03/D/NZ5/06146.

Keywords: bipolar disorder, Brain-Derived Neurotrophic Factor (BDNF), proBDNF, unipolar depression

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401 Modeling Slow Crack Growth under Thermal and Chemical Effects for Fitness Predictions of High-Density Polyethylene Material

Authors: Luis Marquez, Ge Zhu, Vikas Srivastava

Abstract:

High-density polyethylene (HDPE) is one of the most commonly used thermoplastic polymer materials for water and gas pipelines. Slow crack growth failure is a well-known phenomenon in high-density polyethylene material and causes brittle failure well below the yield point with no obvious sign. The failure of transportation pipelines can cause catastrophic environmental and economic consequences. Using the non-destructive testing method to predict slow crack growth failure behavior is the primary preventative measurement employed by the pipeline industry but is often costly and time-consuming. Phenomenological slow crack growth models are useful to predict the slow crack growth behavior in the polymer material due to their ability to evaluate slow crack growth under different temperature and loading conditions. We developed a quantitative method to assess the slow crack growth behavior in the high-density polyethylene pipeline material under different thermal conditions based on existing physics-based phenomenological models. We are also working on developing an experimental protocol and quantitative model that can address slow crack growth behavior under different chemical exposure conditions to improve the safety, reliability, and resilience of HDPE-based pipeline infrastructure.

Keywords: mechanics of materials, physics-based modeling, civil engineering, fracture mechanics

Procedia PDF Downloads 192
400 Dynamics of the Coupled Fitzhugh-Rinzel Neurons

Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

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Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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399 3D Finite Element Analysis for Mechanics of Soil-Tool Interaction

Authors: A. Armin, R. Fotouhi, W. Szyszkowski

Abstract:

This paper is part of a study to develop robots for farming. As such power requirement to operate equipment attach to such robots become an important factor. Soil-tool interaction play major role in power consumption, thus predicting accurately the forces which act on the blade during the farming is prime importance for optimal designing of farm equipment. In this paper a finite element investigation for tillage tools and soil interaction is described by using an inelastic constitutive material law for agriculture application. A 3-dimentional (3D) nonlinear finite element analysis (FEA) is developed to examine behavior of a blade with different rake angles moving in a block of soil, and to estimate the blade force. The soil model considered is an elastic-plastic with non-associated Drucker-Prager material model. Special use of contact elements are employed to consider connection between soil-blade and soil-soil surfaces. The FEA results are compared with experiment ones, which show good agreement in accurately predicting draft forces developed on the blade when it moves through the soil. Also, a very good correlation was obtained between FEA results and analytical results from classical soil mechanics theories for straight blades. These comparisons verified the FEA model developed. For analyzing complicated soil-tool interactions and for optimum design of blades, this method will be useful.

Keywords: finite element analysis, soil-blade contact modeling, blade force, mechanical engineering

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398 Production of Neutrons by High Intensity Picosecond Laser Interacting with Thick Solid Target at XingGuangIII

Authors: Xi Yuan, Xuebin Zhu, Bojun Li

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This work describes the experiment to produce high-intensity pulsed neutron beams on XingGuangIII laser facility. The high-intensity laser is utilized to drive protons and deuterons, which hit a thick solid target to produce neutrons. The pulse duration of the laser used in the experiment is about 0.8 ps, and the laser energy is around 100 J. Protons and deuterons are accelerated from a 10-μm-thick deuterated polyethylene (CD₂) foil and diagnosed by a Thomson parabola ion-spectrometer. The energy spectrum of neutrons generated via ⁷Li(d,n) and ⁷Li(p,n) reaction when proton and deuteron beams hit a 5-mm-thick LiF target is measured by a scintillator-based time-of-flight spectrometer. Results from the neuron measurements show that the maximum neutron energy is about 12.5 MeV and the neutron yield is up to 2×10⁹/pulse. The high-intensity pulsed neutron beams demonstrated in this work can provide a valuable neutron source for material research, fast neutron induced fission research, and so on.

Keywords: picosecond laser driven, fast neutron, time-of-flight spectrometry, XinggungIII

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397 A Neuron Model of Facial Recognition and Detection of an Authorized Entity Using Machine Learning System

Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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396 A Rare Case of Atypical Guillian-Barre Syndrome Following Antecedent Dengue Infection

Authors: Amlan Datta

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Dengue is an arboviral, vector borne infection, quite prevalent in tropical countries such as India. Approximately, 1 to 25% of cases may give rise to neurological complication, such as, seizure, delirium, Guillian-Barre syndrome (GBS), multiple cranial nerve palsies, intracranial thrombosis, stroke-like presentations, to name a few. Dengue fever, as an antecedent to GBS is uncommon, especially in adults.Here, we report a case about a middle aged lady who presented with an acute onset areflexic ascending type of polyradiculoneuropathy along with bilateral lower motor neuron type of facial nerve palsy, as well as abducens and motor component of trigeminal (V3) weakness. Her respiratory and neck muscles were spared. She had an established episode of dengue fever (NS1 and dengue IgM positive) 7 days prior to the weakness. Nerve conduction study revealed a demyelinating polyradiculopathy of both lower limbs and cerebrospinal fluid examination showed albuminocytological dissociation. She was treated with 5 days of intravenous immunoglobulin (IVIg), following which her limb weakness improved considerably. This case highlights GBS as a potential complication following dengue fever.

Keywords: areflexic, demyelinating, dengue, polyradiculoneuropathy

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395 The Concept of Neurostatistics as a Neuroscience

Authors: Igwenagu Chinelo Mercy

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This study is on the concept of Neurostatistics in relation to neuroscience. Neuroscience also known as neurobiology is the scientific study of the nervous system. In the study of neuroscience, it has been noted that brain function and its relations to the process of acquiring knowledge and behaviour can be better explained by the use of various interrelated methods. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales. On the other hand, Neurostatistics based on this study is viewed as a statistical concept that uses similar techniques of neuron mechanisms to solve some problems especially in the field of life science. This study is imperative in this era of Artificial intelligence/Machine leaning in the sense that clear understanding of the technique and its proper application could assist in solving some medical disorder that are mainly associated with the nervous system. This will also help in layman’s understanding of the technique of the nervous system in order to overcome some of the health challenges associated with it. For this concept to be well understood, an illustrative example using a brain associated disorder was used for demonstration. Structural equation modelling was adopted in the analysis. The results clearly show the link between the techniques of statistical model and nervous system. Hence, based on this study, the appropriateness of Neurostatistics application in relation to neuroscience could be based on the understanding of the behavioural pattern of both concepts.

Keywords: brain, neurons, neuroscience, neurostatistics, structural equation modeling

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394 Detecting HCC Tumor in Three Phasic CT Liver Images with Optimization of Neural Network

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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393 Nanomechanical Devices Vibrating at Microwave Frequencies in Simple Liquids

Authors: Debadi Chakraborty, John E. Sader

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Nanomechanical devices have emerged as a versatile platform for a host of applications due to their extreme sensitivity to environmental conditions. For example, mass measurements with sensitivity at the atomic level have recently been demonstrated. Ultrafast laser spectroscopy coherently excite the vibrational modes of metal nanoparticles and permits precise measurement of the vibration characteristics as a function of nanoparticle shape, size and surrounding environment. This study reports that the vibration of metal nanoparticles in simple liquids, like water and glycerol are not described by conventional fluid mechanics, i.e., Navier Stokes equations. The intrinsic molecular relaxation processes in the surrounding liquid are found to have a profound effect on the fluid-structure interaction of mechanical devices at nanometre scales. Theoretical models have been developed based on the non-Newtonian viscoelastic fluid-structure interaction theory to investigate the vibration of nanoparticles immersed in simple fluids. The utility of this theoretical framework is demonstrated by comparison to measurements on single nanowires and ensembles of metal rods. This study provides a rigorous foundation for the use of metal nanoparticles as ultrasensitive mechanical sensors in fluid and opens a new paradigm for understanding extremely high frequency fluid mechanics, nanoscale sensing technologies, and biophysical processes.

Keywords: fluid-structure interaction, nanoparticle vibration, ultrafast laser spectroscopy, viscoelastic damping

Procedia PDF Downloads 259
392 Quantitative Analysis of Presence, Consciousness, Subconsciousness, and Unconsciousness

Authors: Hooshmand Kalayeh

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The human brain consists of reptilian, mammalian, and thinking brain. And mind consists of conscious, subconscious, and unconscious parallel neural-net programs. The primary objective of this paper is to propose a methodology for quantitative analysis of neural-nets associated with these mental activities in the neocortex. The secondary objective of this paper is to suggest a methodology for quantitative analysis of presence; the proposed methodologies can be used as a first-step to measure, monitor, and understand consciousness and presence. This methodology is based on Neural-Networks (NN), number of neuron in each NN associated with consciousness, subconsciouness, and unconsciousness, and number of neurons in neocortex. It is assumed that the number of neurons in each NN is correlated with the associated area and volume. Therefore, online and offline visualization techniques can be used to identify these neural-networks, and online and offline measurement methods can be used to measure areas and volumes associated with these NNs. So, instead of the number of neurons in each NN, the associated area or volume also can be used in the proposed methodology. This quantitative analysis and associated online and offline measurements and visualizations of different Neural-Networks enable us to rewire the connections in our brain for a more balanced living.

Keywords: brain, mind, consciousness, presence, sub-consciousness, unconsciousness, skills, concentrations, attention

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391 Modeling of the Mechanism of Ion Channel Opening of the Visual Receptor's Rod on the Light and Allosteric Effect of Rhodopsin in the Phosphorylation Process

Authors: N. S. Vassilieva-Vashakmadze, R. A. Gakhokidze, I. M. Khachatryan

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In the first part of the paper it is shown that both the depolarization of the cytoplasmic membrane of rods observed in invertebrates and hyperpolarization characteristic of vertebrates on the light may activate the functioning of ion (Na+) channels of cytoplasmic membrane of rods and thus provide the emergence of nerve impulse and its transfer to the neighboring neuron etc. In the second part, using the quantum mechanical program for modeling of the molecular processes, we got a clear picture demonstrating the effect of charged phosphate groups on the protein components of α-helical subunits of the visual rhodopsin receptor. The analysis shows that the phosphorylation of terminal amino acid of seventh α-helical subunits of the visual rhodopsin causes a redistribution of electron density on the atoms, i.e. polarization of subunits, also the changing the configuration of the nuclear subsystem, which corresponds to the deformation process in the molecule. Based on the use of models it can be concluded that this system has an internal relationship between polarization and deformation processes that indicates on the allosteric effect. The allosteric effect is based on quantum-mechanical principle of the self-consistency of the molecules.

Keywords: membrane potential, ion channels, visual rhodopsin, allosteric effect

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390 Deepnic, A Method to Transform Each Variable into Image for Deep Learning

Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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389 Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study

Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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388 Structural Behavior of Non-Prismatic Mono-Symmetric Beam

Authors: Nandini B. Nagaraju, Punya D. Gowda, S. Aishwarya, Benjamin Rohit

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This paper attempts to understand the structural behavior of non-prismatic channel beams subjected to bending through finite element (FE) analysis. The present study aims at shedding some light on how tapered channel beams behave by studying the effect of taper ratio on structural behavior. As a weight reduction is always desired in aerospace structures beams are tapered in order to obtain highest structural efficiency. FE analysis has been performed to study the effect of taper ratio on linear deflection, lateral torsional buckling, non-linear parameters, stresses and dynamic parameters. Taper ratio tends to affect the mechanics of tapered beams innocuously and adversely. Consequently, it becomes important to understand and document the mechanics of channel tapered beams. Channel beams generally have low torsional rigidity due to the off-shear loading. The effect of loading type and location of applied load have been studied for flange taper, web taper and symmetric taper for different conditions. Among these, as the taper ratio is increased, the torsional angular deflection increases but begins to decrease when the beam is web tapered and symmetrically tapered for a mid web loaded beam. But when loaded through the shear center, an increase in the torsional angular deflection can be observed with increase in taper ratio. It should be considered which parameter is tapered to obtain the highest efficiency.

Keywords: channel beams, tapered beams, lateral torsional bucking, shear centre

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387 The Effect of Crack Size, Orientation and Number on the Elastic Modulus of a Cracked Body

Authors: Mark T. Hanson, Alan T. Varughese

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Osteoporosis is a disease affecting bone quality which in turn can increase the risk of low energy fractures. Treatment of osteoporosis using Bisphosphonates has the beneficial effect of increasing bone mass while at the same time has been linked to the formation of atypical femoral fractures. This has led to the increased study of micro-fractures in bones of patients using Bisphosphonate treatment. One of the mechanics related issues which have been identified in this regard is the loss in stiffness of bones containing one or many micro-fractures. Different theories have been put forth using fracture mechanics to determine the effect of crack presence on elastic properties such as modulus. However, validation of these results in a deterministic way has not been forthcoming. The present analysis seeks to provide this deterministic evaluation of fracture’s effect on the elastic modulus. In particular, the effect of crack size, crack orientation and crack number on elastic modulus is investigated. In particular, the Finite Element method is used to explicitly determine the elastic modulus reduction caused by the presence of cracks in a representative volume element. Single cracks of various lengths and orientations are examined as well as cases of multiple cracks. Cracks in tension as well as under shear stress are considered. Although the focus is predominantly two-dimensional, some three-dimensional results are also presented. The results obtained show the explicit reduction in modulus caused by the parameters of crack size, orientation and number noted above. The present results allow the interpretation of the various theories which currently exist in the literature.

Keywords: cracks, elastic, fracture, modulus

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386 Isolated Iterating Fractal Independently Corresponds with Light and Foundational Quantum Problems

Authors: Blair D. Macdonald

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After nearly one hundred years of its origin, foundational quantum mechanics remains one of the greatest unexplained mysteries in physicists today. Within this time, chaos theory and its geometry, the fractal, has developed. In this paper, the propagation behaviour with an iteration of a simple fractal, the Koch Snowflake, was described and analysed. From an arbitrary observation point within the fractal set, the fractal propagates forward by oscillation—the focus of this study and retrospectively behind by exponential growth from a point beginning. It propagates a potentially infinite exponential oscillating sinusoidal wave of discrete triangle bits sharing many characteristics of light and quantum entities. The model's wave speed is potentially constant, offering insights into the perception and a direction of time where, to an observer, when travelling at the frontier of propagation, time may slow to a stop. In isolation, the fractal is a superposition of component bits where position and scale present a problem of location. In reality, this problem is experienced within fractal landscapes or fields where 'position' is only 'known' by the addition of information or markers. The quantum' measurement problem', 'uncertainty principle,' 'entanglement,' and the classical-quantum interface are addressed; these are a problem of scale invariance associated with isolated fractality. Dual forward and retrospective perspectives of the fractal model offer the opportunity for unification between quantum mechanics and cosmological mathematics, observations, and conjectures. Quantum and cosmological problems may be different aspects of the one fractal geometry.

Keywords: measurement problem, observer, entanglement, unification

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385 First Earth Size

Authors: Ibrahim M. Metwally

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Have you ever thought that earth was not the same earth we live on? Was it bigger or smaller? Was it a great continent surrounded by huge ocean as Alfred Wegener (1912) claimed? Earth is the most amazing planet in our Milky Way galaxy and may be in the universe. It is the only deformed planet that has a variable orbit around the sun and the only planet that has water on its surface. How did earth deformation take place? What does cause earth to deform? What are the results of earth deformation? How does its orbit around the sun change? First earth size computation can be achieved only considering the quantum of iron and nickel rested into earth core. This paper introduces a new theory “Earth expansion Theory”. The principles of “Earth Expansion Theory” are leading to new approaches and concepts to interpret whole earth dynamics and its geological and environmental changes. This theory is not an attempt to unify the two divergent dominant theories of continental drift, plate tectonic theory and earth expansion theory. The new theory is unique since it has a mathematical derivation, explains all the change to and around earth in terms of geological and environmental changes, and answers all unanswered questions in other theories. This paper presents the basic of the introduced theory and discusses the mechanism of earth expansion and how it took place, the forces that made the expansion. The mechanisms of earth size change from its spherical shape with radius about 3447.6 km to an elliptic shape of major radius about 6378.1 km and minor radius of about 6356.8 km and how it took place, are introduced and discussed. This article also introduces, in a more realistic explanation the formation of oceans and seas, the preparation of river formation. It also addresses the role of iron in earth size enlargement process within the continuum mechanics framework.

Keywords: earth size, earth expansion, continuum mechanics, continental and ocean formation

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384 Epileptic Seizure Onset Detection via Energy and Neural Synchronization Decision Fusion

Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

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This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

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383 The Foundation Binary-Signals Mechanics and Actual-Information Model of Universe

Authors: Elsadig Naseraddeen Ahmed Mohamed

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In contrast to the uncertainty and complementary principle, it will be shown in the present paper that the probability of the simultaneous occupation event of any definite values of coordinates by any definite values of momentum and energy at any definite instance of time can be described by a binary definite function equivalent to the difference between their numbers of occupation and evacuation epochs up to that time and also equivalent to the number of exchanges between those occupation and evacuation epochs up to that times modulus two, these binary definite quantities can be defined at all point in the time’s real-line so it form a binary signal represent a complete mechanical description of physical reality, the time of these exchanges represent the boundary of occupation and evacuation epochs from which we can calculate these binary signals using the fact that the time of universe events actually extends in the positive and negative of time’s real-line in one direction of extension when these number of exchanges increase, so there exists noninvertible transformation matrix can be defined as the matrix multiplication of invertible rotation matrix and noninvertible scaling matrix change the direction and magnitude of exchange event vector respectively, these noninvertible transformation will be called actual transformation in contrast to information transformations by which we can navigate the universe’s events transformed by actual transformations backward and forward in time’s real-line, so these information transformations will be derived as an elements of a group can be associated to their corresponded actual transformations. The actual and information model of the universe will be derived by assuming the existence of time instance zero before and at which there is no coordinate occupied by any definite values of momentum and energy, and then after that time, the universe begin its expanding in spacetime, this assumption makes the need for the existence of Laplace’s demon who at one moment can measure the positions and momentums of all constituent particle of the universe and then use the law of classical mechanics to predict all future and past of universe’s events, superfluous, we only need for the establishment of our analog to digital converters to sense the binary signals that determine the boundaries of occupation and evacuation epochs of the definite values of coordinates relative to its origin by the definite values of momentum and energy as present events of the universe from them we can predict approximately in high precision it's past and future events.

Keywords: binary-signal mechanics, actual-information model of the universe, actual-transformation, information-transformation, uncertainty principle, Laplace's demon

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382 Diffusion Dynamics of Leech-Heart Inter-Neuron Model

Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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381 Finite Element Molecular Modeling: A Structural Method for Large Deformations

Authors: A. Rezaei, M. Huisman, W. Van Paepegem

Abstract:

Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

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380 Study and Solving High Complex Non-Linear Differential Equations Applied in the Engineering Field by Analytical New Approach AGM

Authors: Mohammadreza Akbari, Sara Akbari, Davood Domiri Ganji, Pooya Solimani, Reza Khalili

Abstract:

In this paper, three complicated nonlinear differential equations(PDE,ODE) in the field of engineering and non-vibration have been analyzed and solved completely by new method that we have named it Akbari-Ganji's Method (AGM) . As regards the previous published papers, investigating this kind of equations is a very hard task to do and the obtained solution is not accurate and reliable. This issue will be emerged after comparing the achieved solutions by Numerical Method. Based on the comparisons which have been made between the gained solutions by AGM and Numerical Method (Runge-Kutta 4th), it is possible to indicate that AGM can be successfully applied for various differential equations particularly for difficult ones. Furthermore, It is necessary to mention that a summary of the excellence of this method in comparison with the other approaches can be considered as follows: It is noteworthy that these results have been indicated that this approach is very effective and easy therefore it can be applied for other kinds of nonlinear equations, And also the reasons of selecting the mentioned method for solving differential equations in a wide variety of fields not only in vibrations but also in different fields of sciences such as fluid mechanics, solid mechanics, chemical engineering, etc. Therefore, a solution with high precision will be acquired. With regard to the afore-mentioned explanations, the process of solving nonlinear equation(s) will be very easy and convenient in comparison with the other methods. And also one of the important position that is explored in this paper is: Trigonometric and exponential terms in the differential equation (the method AGM) , is no need to use Taylor series Expansion to enhance the precision of the result.

Keywords: new method (AGM), complex non-linear partial differential equations, damping ratio, energy lost per cycle

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379 Compaction of Municipal Solid Waste

Authors: Jovana Jankovic Pantic, Dragoslav Rakic, Tina Djuric, Irena Basaric Ikodinovic, Snezana Bogdanovic

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Regardless of the numerous activities undertaken to reduce municipal solid waste, its annual volumes continue to grow. In Serbia, the most common and the only one form of waste disposal is at municipal landfills with daily compaction and soil covering. Municipal waste compacting is one of the basic components of the disposal process. Well compacted waste takes up less volume and allows much safer storage. In order to better predict the behavior of municipal waste at landfills, it is necessary to define compaction parameters: the maximum dry unit weight and optimal moisture content. In current geotechnical practice, the most common method of determination compaction parameters is by the standard method (Proctor compaction test) used in soil mechanics, with an eventual reduction of compaction energy. Although this methodology is accepted in newer geotechnical scientific discipline "waste mechanics", different treatments of municipal waste at the landfill itself (including pretreatment), indicate the need to change this classical approach. The main reason for that is the simulation of the operation of compactors (hedgehogs) at the landfill. Therefore, during the research, various innovative solutions are introduced, such as changing the classic flat Proctor hammer, by adding spikes, whose function is, in addition to compaction, destruction and shredding of municipal waste. The paper presents the behavior of municipal waste for four synthetic waste samples with different waste compositions (Plandište landfill). The samples were tested in standard Proctor apparatus at the same compaction energy, but with two different hammers: standard flat hammer and hammer with spikes.

Keywords: compaction, hammer with spikes, landfill, municipal solid waste, proctor compaction test

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378 The Effect of Fibre Orientation on the Mechanical Behaviour of Skeletal Muscle: A Finite Element Study

Authors: Christobel Gondwe, Yongtao Lu, Claudia Mazzà, Xinshan Li

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Skeletal muscle plays an important role in the human body system and function by generating voluntary forces and facilitating body motion. However, The mechanical properties and behaviour of skeletal muscle are still not comprehensively known yet. As such, various robust engineering techniques have been applied to better elucidate the mechanical behaviour of skeletal muscle. It is considered that muscle mechanics are highly governed by the architecture of the fibre orientations. Therefore, the aim of this study was to investigate the effect of different fibre orientations on the mechanical behaviour of skeletal muscle.In this study, a continuum mechanics approach–finite element (FE) analysis was applied to the left bicep femoris long head to determine the contractile mechanism of the muscle using Hill’s three-element model. The geometry of the muscle was segmented from the magnetic resonance images. The muscle was modelled as a quasi-incompressible hyperelastic (Mooney-Rivlin) material. Two types of fibre orientations were implemented: one with the idealised fibre arrangement, i.e. parallel single-direction fibres going from the muscle origin to insertion sites, and the other with curved fibre arrangement which is aligned with the muscle shape.The second fibre arrangement was implemented through the finite element method; non-uniform rational B-spline (FEM-NURBs) technique by means of user material (UMAT) subroutines. The stress-strain behaviour of the muscle was investigated under idealised exercise conditions, and will be further analysed under physiological conditions. The results of the two different FE models have been outputted and qualitatively compared.

Keywords: FEM-NURBS, finite element analysis, Mooney-Rivlin hyperelastic, muscle architecture

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377 The Contribution of the PCR-Enzymatic Digestion in the Positive Diagnosis of Proximal Spinal Muscular Atrophy in the Moroccan Population

Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

Abstract:

The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene

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376 Simplified Stress Gradient Method for Stress-Intensity Factor Determination

Authors: Jeries J. Abou-Hanna

Abstract:

Several techniques exist for determining stress-intensity factors in linear elastic fracture mechanics analysis. These techniques are based on analytical, numerical, and empirical approaches that have been well documented in literature and engineering handbooks. However, not all techniques share the same merit. In addition to overly-conservative results, the numerical methods that require extensive computational effort, and those requiring copious user parameters hinder practicing engineers from efficiently evaluating stress-intensity factors. This paper investigates the prospects of reducing the complexity and required variables to determine stress-intensity factors through the utilization of the stress gradient and a weighting function. The heart of this work resides in the understanding that fracture emanating from stress concentration locations cannot be explained by a single maximum stress value approach, but requires use of a critical volume in which the crack exists. In order to understand the effectiveness of this technique, this study investigated components of different notch geometry and varying levels of stress gradients. Two forms of weighting functions were employed to determine stress-intensity factors and results were compared to analytical exact methods. The results indicated that the “exponential” weighting function was superior to the “absolute” weighting function. An error band +/- 10% was met for cases ranging from a steep stress gradient in a sharp v-notch to the less severe stress transitions of a large circular notch. The incorporation of the proposed method has shown to be a worthwhile consideration.

Keywords: fracture mechanics, finite element method, stress intensity factor, stress gradient

Procedia PDF Downloads 126