Engineering modelling of structural details of a bridge

This paper presents a method of engineering modelling of structural details, which enables the analysis of local static and dynamic effects in a complex structure with the use of a personal computer. An analysed structural detail, modelled with the use of shell finite elements, is mounted to a spatial truss member system. Then, on the basis of prepared computational model, a static or dynamic analysis is carried out. The proposed model allows to detect the local effects in a theoretical. Conducted analyses confirmed the correct operation of such a computational model. Hence, the method of modelling presented in this paper allows to analyse the local effects on ordinary personal computer and more importantly, the results of such calculations are available within a relatively short period of time. The calculations are carried out by analysing the local effects in a steel node of the truss railway bridge.

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A Cognitive Computational Model Inspired by the Immune System Response

BioMed Research International ◽

10.1155/2014/852181 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15

Author(s):

Mohamed Abdo Abd Al-Hady ◽

Amr Ahmed Badr ◽

Mostafa Abd Al-Azim Mostafa

Keyword(s):

Immune System ◽

Computational Model ◽

Cognitive Architecture ◽

Intelligent Agent ◽

System Response ◽

Danger Theory ◽

Proposed Model ◽

Immune System Response ◽

Fuzzy State

The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.

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Application of Genetic Algorithm on Optimal Pipeline Route Considering Complex Terrains and Obstacles

Volume 3A: Design and Analysis ◽

10.1115/pvp2018-84272 ◽

2018 ◽

Author(s):

Bingyuan Hong ◽

Xiaoping Li ◽

Yu Li ◽

Jingjing Gao ◽

Yanhong Zhou ◽

...

Keyword(s):

Genetic Algorithm ◽

Complex Structure ◽

Genetic Operators ◽

Construction Costs ◽

Gas Field ◽

Proposed Model ◽

Slope Factor ◽

Total Investment ◽

Selection Operators ◽

Novel Model

Gathering network, which is usually characterized by various and complex structure, takes a large proportion of the overall construction cost of gas field. Optimization of pipeline routes is an effective way to reduce the investment. In this paper, a novel model for optimal route of pipeline considering complex terrains and obstacles is proposed and solved by Genetic Algorithm. Minimizing the total investment is the object of this model. Since the construction costs under different terrains are different, the distance factor Li, slope factor Di and elastic factor Si are introduced into the objective function to represent the length of the pipeline, the gradient of the pipeline, and the fluctuation of terrain. In addition, the performance of the model is verified by taking three typical situations of different terrains and obstacles as examples. The results illustrate that the proposed model can address the optimal design of pipeline routes in complex terrains. Moreover, the effects of different genetic operators on solutions are investigated, including three selection operators and two crossover operators. The study provides a guideline for designing pipeline routes in complex terrains and is also applicable to the analogous problem.

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Quasi-PSO Algorithm for Modeling Foraging Dynamics in Social Mammals

International Journal of Agent Technologies and Systems ◽

10.4018/jats.2011010103 ◽

2011 ◽

Vol 3 (1) ◽

pp. 27-38

Author(s):

Marco Campenní ◽

Federico Cecconi

Keyword(s):

Computational Model ◽

Animal Behavior ◽

Pso Algorithm ◽

Social Phenomenon ◽

Proposed Model

In this paper, the authors present a computational model of a fundamental social phenomenon in the study of animal behavior: the foraging. The purpose of this work is, first, to test the validity of the proposed model compared to another existing model, the flocking model; then, to try to understand whether the model may provide useful suggestions in studying the size of the group in some species of social mammals.

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A neural and computational model for the chromatic control of accommodation

Visual Neuroscience ◽

10.1017/s0952523800000705 ◽

1990 ◽

Vol 5 (6) ◽

pp. 547-555 ◽

Cited By ~ 38

Author(s):

D. I. Flitcroft

Keyword(s):

Image Quality ◽

Computational Model ◽

Cortical Neurons ◽

Chromatic Aberration ◽

Refractive State ◽

Spatial Frequencies ◽

Proposed Model ◽

Band Pass ◽

Chromatic Cues ◽

Chromatic Processing

AbstractAccommodation is more accurate with polychromatic stimuli than with narrowband or monochromatic stimuli. The aim of this paper is to develop a computational model for how the visual system uses the extra information in polychromatic stimuli to increase the accuracy of accommodation responses. The proposed model is developed within the context of both trichromacy and also the organization of spatial and chromatic processing within the visual cortex.The refractive error present in the retinal image can be estimated by comparing image quality with and without small additional changes in refractive state. In polychromatic light, the chromatic aberration of the eye results in differences in ocular refractive power for light of different wavelengths. As a result, the refractive state of the eye can be estimated by comparing image quality in the three types of cone photoreceptor. The ability of cortical neurons to perform such comparisons on image quality with a crude form of spatial-frequency analysis is examined theoretically. It is found that spatially band-pass chromatically opponent neurons (that may correspond to double opponent neurons) can perform such calculations and that chromatic cues to accommodation are extracted most effectively by neurons responding to spatial frequencies of between 2 and 8 cycles/deg.

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Determination of Material/Geometry of the Section Most Adequate for a Static Loaded Beam Subjected to a Combination of Bending and Torsion

Materials Science Forum ◽

10.4028/www.scientific.net/msf.730-732.507 ◽

2012 ◽

Vol 730-732 ◽

pp. 507-512 ◽

Cited By ~ 3

Author(s):

Hugo Miguel Silva ◽

José Filipe Bizarro de Meireles

Keyword(s):

Finite Element ◽

Material Properties ◽

Model Updating ◽

Material Selection ◽

Young Modulus ◽

Element Model ◽

Mechanical Tests ◽

Correct Operation ◽

Short Period ◽

Relevant Material

The acceleration of industrial machines mobile parts has been increasing over the last few years, due to the need of higher production in a short period of time. The machines were dimensioned for a lower value of acceleration, which means there is not enough rigidity for the correct operation at much higher accelerations. Nowadays, the accelerations can be near 12 times the acceleration of gravity. There is the need of improving rigidity to make possible the correct machine operation without undesired vibrations that can ultimately lead to failure. The main applications of this work are plotters and laser cutting machines. To improve rigidity, one must improve the relevant material properties, and the relevant geometric variables of the model.[1] A novel Finite Element Model Updating methodology is presented in this paper. The considered models were : a ribbed plate and a tubular beam. The models were built by means of the Finite Element Method (FEM), and MATLAB was used to control the optimization process, using a programming code. Both material properties and geometric parameters were optimized. The main aim of the materials modeling is to know how the value of the objective function changes with the value of the material properties. Materials selection was performed, using material selection charts, to select the best material for the application. The value of these properties was not in the catalogue, and the properties used to perform the material selection were related to a material sub-class, Eg. Steel. The final material selection determined the best specific material for the application, and that material was mechanically tested. The mechanical tests performed were: Tensile Test and Extensometry Test, to obtain the relevant material properties, mainly Young Modulus, Poisson Coefficient and Yield Stress. The deflection of the optimized models reduced strongly in comparison to the initial models.

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High-order fluxes in heat transfer with phonons and electrons: application towavepropagation

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2021.0392 ◽

2021 ◽

Vol 477 (2253) ◽

pp. 20210392

Author(s):

I. Carlomagno ◽

M. Di Domenico ◽

A. Sellitto

Keyword(s):

Heat Transfer ◽

Irreversible Thermodynamics ◽

High Order ◽

Lattice Vibrations ◽

Thermal Waves ◽

Local Effects ◽

Proposed Model ◽

Non Local ◽

Study Heat Transfer ◽

Heat Carriers

We propose a theoretical model to study heat transfer at the nanoscale by means of high-order thermodynamic fluxes. The model is fully compatible with the model of heat transfer of extended irreversible thermodynamics, represents a generalization of the Guyer–Krumhansl proposal (Guyer & Krumhansl 1966 Phys. Rev. 148 ) and is able to deal with relaxational and non-local effects. It also accounts for the role played by the different heat carriers (electrons and/or lattice vibrations) and captures different heat-carrier temperatures. The proposed model is hyperbolic and is used to investigate the propagation of thermal waves.

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Variational level set image segmentation model coupled with kernel distance function

Journal of Algorithms & Computational Technology ◽

10.1177/1748302620931421 ◽

2020 ◽

Vol 14 ◽

pp. 174830262093142 ◽

Cited By ~ 1

Author(s):

Noor Badshah ◽

Ali Ahmad ◽

Fazli Rehman

Keyword(s):

Image Segmentation ◽

Euclidean Distance ◽

Complex Structure ◽

Intensity Inhomogeneity ◽

Distance Metrics ◽

Proposed Model ◽

Severe Intensity ◽

Kernel Distance ◽

Variational Level Set ◽

Better Than

One of the crucial challenges in the area of image segmentation is intensity inhomogeneity. For most of the region-based models, it is not easy to completely segment images having severe intensity inhomogeneity and complex structure, as they rely on intensity distributions. In this work, we proposed a firsthand hybrid model by blending kernel and Euclidean distance metrics. Experimental results on some real and synthetic images suggest that our proposed model is better than models of Chan and Vese, Wu and He, and Salah et al.

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Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments

International Journal of Multimedia Data Engineering and Management ◽

10.4018/ijmdem.2021040103 ◽

2021 ◽

Vol 12 (2) ◽

pp. 31-56

Author(s):

Wei Wang ◽

Hui Liu ◽

Wangqun Lin

Keyword(s):

Control Strategy ◽

Source Information ◽

Proposed Model ◽

Short Period ◽

Air Combat ◽

Multi Agent ◽

Agent Control ◽

Simulation Results ◽

Combat Environment ◽

Tree Method

In the rapidly changing air combat environment, it is quite difficult for pilots to make speedy and reasonable decisions in a very short period due to lack of experience and the uncertainty of perception situation. Hence, the authors propose an intelligent cognitive tactical strategy framework of air combat on multi-source information in uncertain air combat situations for decision support. A fuzzy inferring tree method is proposed to simulate human intellection. Then, to further improve the accuracy of the reasoning results, a genetic algorithm is introduced to optimize the structure and parameters of fuzzy rules. The simulation results show that the proposed model is reasonable, fast, accurate, repeatable, and fatigue-free, which lays a good foundation for future high-end unmanned combat explorations.

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Dissociable Forms of Repetition Priming: A Computational Model

Neural Computation ◽

10.1162/neco_a_00569 ◽

2014 ◽

Vol 26 (4) ◽

pp. 712-738 ◽

Cited By ~ 1

Author(s):

Kirill Makukhin ◽

Scott Bolland

Keyword(s):

Computational Model ◽

Neural Activity ◽

Repetition Priming ◽

Hebbian Learning ◽

Neural Mechanisms ◽

Stimulus Repetition ◽

Repetition Suppression ◽

Opposite Trend ◽

Proposed Model ◽

The Brain

Nondeclarative memory and novelty processing in the brain is an actively studied field of neuroscience, and reducing neural activity with repetition of a stimulus (repetition suppression) is a commonly observed phenomenon. Recent findings of an opposite trend—specifically, rising activity for unfamiliar stimuli—question the generality of repetition suppression and stir debate over the underlying neural mechanisms. This letter introduces a theory and computational model that extend existing theories and suggests that both trends are, in principle, the rising and falling parts of an inverted U-shaped dependence of activity with respect to stimulus novelty that may naturally emerge in a neural network with Hebbian learning and lateral inhibition. We further demonstrate that the proposed model is sufficient for the simulation of dissociable forms of repetition priming using real-world stimuli. The results of our simulation also suggest that the novelty of stimuli used in neuroscientific research must be assessed in a particularly cautious way. The potential importance of the inverted-U in stimulus processing and its relationship to the acquisition of knowledge and competencies in humans is also discussed.

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