MATHEMATICAL MODELING OF MESO-TIDAL BARRIER ISLAND COASTS Part II: PROCESS-BASED SIMULATION MODELS

The use of computer simulation experiments as a tool for working with theories is not as widespread in sociology as it is in most scientific disciplines. This brief article explains how modeling is a distinctive activity from either “theory” or “empirical analysis” but how it informs both and connects them. Simulation models are artificial objects created to translate theoretical generalizations into specific scenarios involving states (variables and/or actors) and rates (the dynamic causal laws hypothesized to generate change over time in the states). Simulation models are analyzed to understand the full range of implications of theoretical statements as they apply to producing historical realizations under particular circumstances. Simulation analysis operates by a method of experimentation, unlike mathematical modeling and statistical modeling. The strengths and limitations of these three approaches to studying models are discussed, and suggested to be complementary rather than competitive with each other. Last, this article briefly points out some of the unique features of the exemplars that compose the remainder of this special issue of Sociological Perspectives.

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Computer simulation in informatics lessons as a factor of the continuity of school education in teaching mathematical modeling

Informatics and Education ◽

10.32517/0234-0453-2021-36-5-52-58 ◽

2021 ◽

pp. 52-58

Author(s):

M. E. Korolev

Keyword(s):

Mathematical Modeling ◽

Engineering Students ◽

Applied Mathematics ◽

Simulation Models ◽

Interactive Learning Environments ◽

School Education ◽

Mathematical Education ◽

Transport Direction ◽

Using Data ◽

Academy Of Sciences

The article actualizes the need to use elements of computer modeling from school to university when teaching mathematics to engineering students, analyzes the role of simulation models of applied mathematics. The experience of organizing classes using data visualization is presented, the use of simulators and games for studying mathematics in the context of mathematical education, in which students interact with interactive learning environments, is discussed, examples of using computer simulations in the classroom are discussed. The study lists and characterizes the types of didactic simulations, examines the process of transition of school education using simulators and games into the didactics of mathematics of technical universities using applied mathematics and mathematical modeling to elements of simulation. A pedagogical experiment of the continuity of school education (section “Information systems and programming” of the Donetsk Republican Small Academy of Sciences for Students) was carried out in teaching applied mathematics, informatics and mathematical modeling (the department “Transport technologies”) students of the engineering and transport direction of Automobile and Road Institute of Donetsk National Technical University.

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MATHEMATICAL MODELING OF ELECTRICAL RESISTIVITY OF ESR SLAG

Litiyo i Metallurgiya (FOUNDRY PRODUCTION AND METALLURGY) ◽

10.21122/1683-6065-2017-1-21-25 ◽

2017 ◽

pp. 21-25

Author(s):

O. S. Ivanova ◽

V. N. Rybak

Keyword(s):

Mathematical Modeling ◽

Electrical Resistivity ◽

Mathematical Models ◽

Simulation Models ◽

Computer Programs

The mathematical models of the electrical resistivity of ESR slag dependence on their composition and temperature are developed. The calculated models are tested for adequacy and can be used in engineering calculations and computer programs, APCS, simulation models and computer programs that permit quickly and accurately determine the parameters of slag in their composition and temperature, as well as to select the composition of slag for the specified parameters.

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Fire Modeling

Volume 6: 16th Computers in Engineering Conference ◽

10.1115/96-detc/cie-1349 ◽

1996 ◽

Author(s):

David G. Lilley

Keyword(s):

Mathematical Modeling ◽

Experimental Approach ◽

Simulation Models ◽

Fire Modeling ◽

Site Investigations ◽

Toxic Gases ◽

Smoke Layer ◽

Fire Scenarios ◽

Key Features ◽

Witness Statements

Abstract The mathematical modeling approach to simulating fire development in a multi-room building complements the experimental approach and/or post-fire on-site investigations. Fire simulation models provide estimates of the amount and temperature of the smoke layer produced, the evolution of toxic gases, and the amount of time available from the onset of fire for the safe departure of occupants. Results can be used to determine the key features of the fire evolution and the corresponding danger to occupants. Studies of this type help to validate or deny the suggested fire scenario and witness statements. Fire modeling thus helps to discriminate between alternative fire scenarios by evaluating the consequences and comparing them with observations.

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MATHEMATICAL MODELING OF MESO-TIDAL BARRIER ISLAND COASTS Part I: EMPIRICAL AND SEMI-EMPIRICAL MODELS

Advances in Coastal and Ocean Engineering ◽

10.1142/9789812797575_0003 ◽

1996 ◽

pp. 115-149 ◽

Cited By ~ 15

Author(s):

HUIB J. DE VRIEND

Keyword(s):

Mathematical Modeling ◽

Barrier Island ◽

Empirical Models ◽

Semi Empirical

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Correlation of Pore Structure and Permeability by SEM-Image Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100180896 ◽

1990 ◽

Vol 48 (1) ◽

pp. 428-429

Author(s):

C. A. Callender ◽

Wm. C. Dawson ◽

J. J. Funk

Keyword(s):

Image Analysis ◽

Pore Structure ◽

Imaging System ◽

Pore Space ◽

Simulation Models ◽

Image Analyzer ◽

Imaging Data ◽

Sem Images ◽

Thin Sections ◽

Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

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