Relevant bibliographies by topics / Mathematical modelling methodologies

Academic literature on the topic 'Mathematical modelling methodologies'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Mathematical modelling methodologies"

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Kvasha, Serhii, Nadiia Davydenko, Yurii Pasichnyk, Tetiana Viatkina, and Natalia Wasilewska. "GDP modelling: assessment of methodologies and peculiarities of its usage in Ukraine." Problems and Perspectives in Management 16, no. 4 (November 9, 2018): 186–200. http://dx.doi.org/10.21511/ppm.16(4).2018.16.

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GDP is one of the main indicators determining the level of economic growth in countries and regions across the globe, therefore, its calculation should be based on the advanced methodology. In the present context, the existing methods of the GDP calculation do not fully meet the fineness criterion subject to certain objective and subjective reasons. Hence, the development of more perfect methodology that takes into account the disadvantages of the existing techniques and is based on economic and mathematical modeling is an urgent national task for Ukraine. The purpose of the article is to assess the GDP calculation methodology used in Ukraine. To achieve this purpose, the relevant methods of GDP calculation, which are valid in Ukraine, have been analyzed, their specifics, certain drawbacks, problems of use and application scenarios have been also revealed. According to the analysis results, an advanced methodology based on an economic and mathematical model with the use of dynamic programming is proposed. The developed methodology for calculating the GDP takes into account the peculiarities of social development in Ukraine and the tendencies of world economic processes and contributes to obtaining more reliable GDP values. It will be useful for experts in financial institutions, including international ones, and scholars working in the macroeconomic modeling area.
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Ferrer, Jordi, Clara Prats, Daniel López, and Josep Vives-Rego. "Mathematical modelling methodologies in predictive food microbiology: A SWOT analysis." International Journal of Food Microbiology 134, no. 1-2 (August 31, 2009): 2–8. http://dx.doi.org/10.1016/j.ijfoodmicro.2009.01.016.

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Bertozzi, Andrea L., Shane D. Johnson, and Michael J. Ward. "Mathematical modelling of crime and security: Special Issue of EJAM." European Journal of Applied Mathematics 27, no. 3 (April 28, 2016): 311–16. http://dx.doi.org/10.1017/s0956792516000176.

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This special issue of the European journal of applied mathematics features research articles that involve the application of mathematical methodologies to the modelling of a broad range of problems related to crime and security. Some specific topics in this issue include recent developments in mathematical models of residential burglary, a dynamical model for the spatial spread of riots initiated by some triggering event, the analysis and development of game-theoretic models of crime and conflict, the study of statistically based models of insurgent activity and terrorism using real-world data sets, models for the optimal strategy of police deployment under realistic constraints, and a model of cyber crime as related to the study of spiking behaviour in social network cyberspace communications. Overall, the mathematical and computational methodologies employed in these studies are as diverse as the specific applications themselves and the scales (spatial or otherwise) to which they are applied. These methodologies range from statistical and stochastic methods based on maximum likelihood methods, Bayesian equilibria, regression analysis, self-excited Hawkes point processes, agent-based random walk models on networks, to more traditional applied mathematical methods such as dynamical systems and stability theory, the theory of Nash equilibria, rigorous methods in partial differential equations and travelling wave theory, and asymptotic methods that exploit disparate space and time scales.
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Guergachi, A. Aziz, and Gilles G. Patry. "Identification, verification and validation of process models in wastewater engineering: a critical review." Journal of Hydroinformatics 5, no. 3 (July 1, 2003): 181–88. http://dx.doi.org/10.2166/hydro.2003.0014.

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This article presents a critical review of the existing methodologies for process mathematical modelling in the area of wastewater engineering. It is argued that model identifiability is not a major issue in mathematical modelling. Model verifiability is a very demanding criterion that can be replaced by a less stringent one: model observability. The issue of ‘complex models versus reduced-order models’ is to be resolved by introducing a new concept: optimal model complexity. The traditional procedures of model validation are not adequate and a mathematical framework for model quality evaluation is needed.
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Et. al., Kaustubh Kulkarni ,. "MATHEMATICAL MODELLING OF A CIRCULAR CENTRAL SOLAR RECEIVER WITH VARIABLE DIAMETER HEADER." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (March 26, 2021): 519–26. http://dx.doi.org/10.17762/itii.v9i2.379.

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The circular central solar receiver helps in the generation of power output in a solar power plant. This paper of research encompasses mathematical development and modelling of a circular central solar receiver with variable diameter header. This modelling is utilized for analyzing the power output in a year. A desired electrical output is generated by the modeling. Methodologies were utilized for evaluating the desired parameters involved in the modelling of the entire system such as; size of the receiver, height of the tower etc. In this modelling system, solar simulator is utilized in the place of heliostat. The working fluid in the system is water. The type of receiver involved in the modelling is a circular central solar receiver. Simulation of the thermal solar receiver system is done. The solar irradiation heat flux of 3500 W/m2 is applied at the input.
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McKemmish, Laura K., and Jonathan Tennyson. "General mathematical formulation of scattering processes in atom–diatomic collisions in the RmatReact methodology." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2154 (August 5, 2019): 20180409. http://dx.doi.org/10.1098/rsta.2018.0409.

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Accurately modelling cold and ultracold reactive collisions occurring over deep potential wells, such as D + + H 2 → H + + HD , requires the development of new theoretical and computational methodologies. One potentially useful framework is the R -matrix method adopted widely for electron–molecule collisions which has more recently been applied to non-reactive heavy-particle collisions such as Ar–Ar. The existing treatment of non-reactive elastic and inelastic scattering needs to be substantially extended to enable modelling of reactive collisions: this is the subject of this paper. Herein, we develop the general mathematical formulation for non-reactive elastic and inelastic scattering, photoassociation, photodissociation, charge exchange and reactive scattering using the R -matrix method. Of particular note is that the inner region, of central importance to calculable R -matrix methodologies, must be finite in all scattering coordinates rather than a single scattering coordinate as for non-reactive scattering. This article is part of a discussion meeting issue ‘Advances in hydrogen molecular ions: H 3 + , H 5 + and beyond’.
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Piskur, Pawel, Piotr Szymak, and Bartosz Larzewski. "Shipyard Crane Modeling Methods." Pedagogika-Pedagogy 93, no. 6s (August 31, 2021): 279–90. http://dx.doi.org/10.53656/ped21-6s.25shi.

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The article discusses various crane mathematical modelling and simulation methodologies. The purpose of this study is to assess the effect of wind force on the dynamic of shipyard cranes, particularly hook movements in the horizontal plane. Appropriate simulation models are required to offer a robust control strategy that allows the crane to be remotely operated in windy circumstances. As a result, mathematical models based on differential equations for varying numbers of independent variables are compared to object-oriented, physical modelling model based on Matlab Simscape Multibody. The assumptions are explored, as well as the effect of the number of independent variables on model correctness.
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Nacaskul, Poomjai. "Survey of credit risk models in relation to capital adequacy framework for financial institutions." Journal of Governance and Regulation 5, no. 4 (2016): 68–84. http://dx.doi.org/10.22495/jgr_v5_i4_p6.

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This article (i) iterates what is meant by credit risks and the mathematical-statistical modelling thereof, (ii) elaborates the conceptual and technical links between credit risk modelling and capital adequacy framework for financial institutions, particularly as per the New Capital Accord (Basel II)’s Internal Ratings-Based (IRB) approach, (iii) proffer a simple and intuitive taxonomy on contemporary credit risk modelling methodologies, and (iv) discuses in some details a number of key models pertinent, in various stages of development, to various application areas in the banking and financial sector.
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Barons, Martine Jayne, and Rachel L. Wilkerson. "Proof and Uncertainty in Causal Claims." Exchanges: The Interdisciplinary Research Journal 5, no. 2 (June 7, 2018): 72–89. http://dx.doi.org/10.31273/eirj.v5i2.238.

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Causal questions drive scientific enquiry. From Hume to Granger, and Rubin to Pearl the history of science is full of examples of scientists testing new theories in an effort to uncover causal mechanisms. The difficulty of drawing causal conclusions from observational data has prompted developments in new methodologies, most notably in the area of graphical models. We explore the relationship between existing theories about causal mechanisms in a social science domain, new mathematical and statistical modelling methods, the role of mathematical proof and the importance of accounting for uncertainty. We show that, while the mathematical sciences rely on their modelling assumptions, dialogue with the social sciences calls for continual extension of these models. We show how changing model assumptions lead to innovative causal structures and more nuanced casual explanations. We review differing techniques for determining cause in different disciplines using causal theories from psychology, medicine, and economics.
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Anisimov, A. L., and Yu B. Melnikov. "On the Methodologies for Evaluation of Tax Authorities’ Performance from the Perspective of Economic-Mathematical Modelling." Journal of the Ural State University of Economics 69 (2017): 78–90. http://dx.doi.org/10.29141/2073-1019-2017-13-1-6.

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Dissertations / Theses on the topic "Mathematical modelling methodologies"

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Gill, Mandeep Singh. "Application of software engineering methodologies to the development of mathematical biological models." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:35178f3a-7951-4f1c-aeab-390cdd622b05.

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Mathematical models have been used to capture the behaviour of biological systems, from low-level biochemical reactions to multi-scale whole-organ models. Models are typically based on experimentally-derived data, attempting to reproduce the observed behaviour through mathematical constructs, e.g. using Ordinary Differential Equations (ODEs) for spatially-homogeneous systems. These models are developed and published as mathematical equations, yet are of such complexity that they necessitate computational simulation. This computational model development is often performed in an ad hoc fashion by modellers who lack extensive software engineering experience, resulting in brittle, inefficient model code that is hard to extend and reuse. Several Domain Specific Languages (DSLs) exist to aid capturing such biological models, including CellML and SBML; however these DSLs are designed to facilitate model curation rather than simplify model development. We present research into the application of techniques from software engineering to this domain; starting with the design, development and implementation of a DSL, termed Ode, to aid the creation of ODE-based biological models. This introduces features beneficial to model development, such as model verification and reproducible results. We compare and contrast model development to large-scale software development, focussing on extensibility and reuse. This work results in a module system that enables the independent construction and combination of model components. We further investigate the use of software engineering processes and patterns to develop complex modular cardiac models. Model simulation is increasingly computationally demanding, thus models are often created in complex low-level languages such as C/C++. We introduce a highly-efficient, optimising native-code compiler for Ode that generates custom, model-specific simulation code and allows use of our structured modelling features without degrading performance. Finally, in certain contexts the stochastic nature of biological systems becomes relevant. We introduce stochastic constructs to the Ode DSL that enable models to use Stochastic Differential Equations (SDEs), the Stochastic Simulation Algorithm (SSA), and hybrid methods. These use our native-code implementation and demonstrate highly-efficient stochastic simulation, beneficial as stochastic simulation is highly computationally intensive. We introduce a further DSL to model ion channels declaratively, demonstrating the benefits of DSLs in the biological domain. This thesis demonstrates the application of software engineering methodologies, and in particular DSLs, to facilitate the development of both deterministic and stochastic biological models. We demonstrate their benefits with several features that enable the construction of large-scale, reusable and extensible models. This is accomplished whilst providing efficient simulation, creating new opportunities for biological model development, investigation and experimentation.
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Niklewski, Jacek. "Multivariate GARCH and portfolio optimisation : a comparative study of the impact of applying alternative covariance methodologies." Thesis, Coventry University, 2014. http://curve.coventry.ac.uk/open/items/a8d7bf49-198d-49f2-9894-12e22ce2d7f1/1.

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This thesis investigates the impact of applying different covariance modelling techniques on the efficiency of asset portfolio performance. The scope of this thesis is limited to the exploration of theoretical aspects of portfolio optimisation rather than developing a useful tool for portfolio managers. Future work may entail taking the results from this work further and producing a more practical tool from a fund management perspective. The contributions made by this thesis to the knowledge of the subject are that it extends literature by applying a number of different covariance models to a unique dataset that focuses on the 2007 global financial crisis. The thesis also contributes to the literature as the methodology applied also enables a distinction to be made in respect to developed and emerging/frontier regional markets. This has resulted in the following findings: First, it identifies the impact of the 2007–2009 financial crisis on time-varying correlations and volatilities as measured by the dynamic conditional correlation model (Engle 2002). This is examined from the perspective of a United States (US) investor given that the crisis had its origin in the US market. Prima facie evidence is found that economic structural adjustment has resulted in long-term increases in the correlation between the US and other markets. In addition, the magnitude of the increase in correlation is found to be greater in respect to emerging/frontier markets than in respect to developed markets. Second, the long-term impact of the 2007–2009 financial crisis on time-varying correlations and volatilities is further examined by comparing estimates produced by different covariance models. The selected time-varying models (DCC, copula DCC, GO-GARCH: MM, ICA, NLS, ML; EWMA and SMA) produce statistically significantly different correlation and volatility estimates. This finding has potential implication for the estimation of efficient portfolios. Third, the different estimates derived using the selected covariance models are found to have a significant impact on the calculated weights and turnovers of efficient portfolios. Interestingly, however, there was no significant difference between their respective returns. This is the main finding of the thesis, which has potentially very important implications for portfolio management.
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Nourmohammadzadeh, Abtin [Verfasser], Sven [Akademischer Betreuer] Hartmann, and Stefan [Akademischer Betreuer] Westphal. "Mathematical modelling with exact, heuristic and meta-heuristic solution methodologies for the fuel-efficient platooning of heavy duty vehicles on road networks / Abtin Nourmohammadzadeh ; Sven Hartmann, Stefan Westphal." Clausthal-Zellerfeld : Technische Universität Clausthal, 2019. http://d-nb.info/1231362839/34.

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Sebolai, David Selokela. "Modelling and forecasting student enrolment with Box -Jenkins and Holty-Winters methodologies : a case of North West University, Mafikeng Campous / David Selokela Sebolai." Thesis, 2010. http://hdl.handle.net/10394/16020.

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Books on the topic "Mathematical modelling methodologies"

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Urban geography: An analytical approach. Upper Saddle River, N.J: Prentice Hall, 1996.

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Methodologies for Service Life Prediction of Buildings: With a Focus on Façade Claddings. Springer, 2016.

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Brito, Jorge de, Ana Silva, and Pedro Lima Gaspar. Methodologies for Service Life Prediction of Buildings: With a Focus on Façade Claddings. Springer London, Limited, 2016.

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Brito, Jorge de, Ana Silva, and Pedro Lima Gaspar. Methodologies for Service Life Prediction of Buildings: With a Focus on Façade Claddings. Springer International Publishing AG, 2018.

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Book chapters on the topic "Mathematical modelling methodologies"

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Brusa, L. "Mathematical Modelling of Structural Industrial Problems: Methodologies and Algorithms." In Applied and Industrial Mathematics, 359–67. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-1908-2_31.

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Höskuldsson, Agnar. "Applications of the H-Principle of Mathematical Modelling." In Advances in Statistical Methodologies and Their Application to Real Problems. InTech, 2017. http://dx.doi.org/10.5772/66153.

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Yeomans, Julian Scott. "A Nature-Inspired Metaheuristic Approach for Generating Alternatives." In Advanced Methodologies and Technologies in Business Operations and Management, 722–33. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7362-3.ch054.

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“Real-world” decision making often involves complex problems that are riddled with incompatible and inconsistent performance objectives. These problems typically possess competing design requirements which are very difficult—if not impossible—to quantify and capture at the time that any supporting decision models are constructed. There are invariably unmodeled design issues, not apparent during the time of model construction, which can greatly impact the acceptability of the model's solutions. Consequently, when solving many practical mathematical programming applications, it is generally preferable to formulate numerous quantifiably good alternatives that provide very different perspectives to the problem. This solution approach is referred to as modelling to generate alternatives (MGA). This study demonstrates how the nature-inspired firefly algorithm can be used to efficiently create multiple solution alternatives that both satisfy required system performance criteria and yet are maximally different in their decision spaces.
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Jujjavarapu, Satya Eswari, and Bikesh Kumar Singh. "Optimization Techniques Applications in Biochemical Engineering and Controlled Drug Delivery." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 609–19. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch031.

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Before starting semi-pilot/pilot production plants for biochemical metabolites production, it is essential to optimize the fermentation media. This chapter discusses the classical and advanced techniques of media optimization. The statistical approaches save experimental time for developing processing and improving quality. Recent years have seen the growth of integrated approaches of microbial cultures. Optimization techniques such as response surface methodology, artificial neural network, genetic algorithms, differential evolution, ant colony optimization, etc. have received attention recently because of their major applications in various fields. Controlled release formulations have so many versatile applications in the field of pharmaceutical drugs that they have become important tools to apply the modern concept of therapeutic treatment. Process optimization of such formulations, mathematical modelling can play an important role. This chapter discusses various methodologies for optimization of formulation conditions for drug delivery.
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Jujjavarapu, Satya Eswari, and Bikesh Kumar Singh. "Optimization Techniques Applications in Biochemical Engineering and Controlled Drug Delivery." In Advances in Medical Technologies and Clinical Practice, 180–90. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4969-7.ch008.

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Before starting semi-pilot/pilot production plants for biochemical metabolites production, it is essential to optimize the fermentation media. This chapter discusses the classical and advanced techniques of media optimization. The statistical approaches save experimental time for developing processing and improving quality. Recent years have seen the growth of integrated approaches of microbial cultures. Optimization techniques such as response surface methodology, artificial neural network, genetic algorithms, differential evolution, ant colony optimization, etc. have received attention recently because of their major applications in various fields. Controlled release formulations have so many versatile applications in the field of pharmaceutical drugs that they have become important tools to apply the modern concept of therapeutic treatment. Process optimization of such formulations, mathematical modelling can play an important role. This chapter discusses various methodologies for optimization of formulation conditions for drug delivery.
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Conference papers on the topic "Mathematical modelling methodologies"

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"Application of Mathematical Modelling for Simulation of Galvanic Corrosion." In 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004588504610466.

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"Mathematical Modelling of Smooth and Precise Adaptive Train Braking System." In 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004592602040209.

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Stefanova Nikolova, Gergana, Vladimir Konstantinov Kotev, and Daniel Marinov Dantchev. "Computer and Mathematical Modelling of the Female Human Body: Determination of Mass-inertial Characteristics in Basic Body Positions." In 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006480304160421.

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Watton, Paul N., Marc Homer, Justin Penrose, Harry Thompson, Haoyu Chen, Alisa Selimovic, and Yiannis Ventikos. "Patient-Specific Modelling of Intracranial Aneurysm Evolution." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53223.

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Intracranial aneurysms appear as sac-like outpouchings of the cerebral vasculature wall; inflated by the pressure of the blood that fills them. They are relatively common and affect up to 5% of the adult population. Fortunately, most remain asymptomatic. However, there is a small but inherent risk of rupture: 0.1% to 1% of detected aneurysms rupture every year. If rupture does occur there is a 30% to 50% chance of fatality. Consequently, if an aneurysm is detected, clinical intervention may be deemed appropriate. Therapy is currently aimed at pre-rupture detection and preventative treatment. However, interventional procedures are not without risk to the patient. The improvement and optimization of interventional techniques is an important concern for patient welfare and is necessary for rationalisation of healthcare priorities. Hence there is a need to develop methodologies to assist in identifying those ICAs most at risk of rupture. We focus on the mathematical modelling and computational simulation of ICA evolution. Models must take into consideration: (i) the biomechanics of the arterial wall; (ii) the biology of the arterial wall and (iii) the complex interplay between (i) and (ii), i.e. the mechanobiology of the arterial wall. The ultimate ambition of such models is to aid clinical diagnosis on a patient-specific basis. However, due to the significant biological complexity coupled with limited histological information such models are still in their relative infancy. Current research focuses on simulating the evolution of an ICA with an aim to yield insight into the growth and remodelling (G&R) processes that give rise to inception, enlargement, stabilisation and rupture. We present a novel Fluid-Structure-Growth computational framework for modelling aneurysm evolution.
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Hajžman, Michal, Luděk Pešek, Jan Brůha, Vladimír Zeman, and Drahomír Rychecký. "Basic Optimization Methodology for the Design of Friction Damping in Blade Shrouds." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13443.

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This paper is focused on the optimization of friction element parameters in blade shrouds for various types of excitation. In order to create and validate a proper modelling methodology an experimental stand and a numerical simulation of blades interaction by means of a friction element placed in the shrouds were prepared. Mathematical models are based on the finite element method combined with rigid bodies. The interaction of the friction element and blades is described by normal contact and tangential friction forces derived for particular geometrical parameters of the studied mechanical system. The models can be analyzed both in frequency domain (by the harmonic balance method) or in time domain (by the numerical integration). The results of the optimization of friction element parameters with respect to the bending vibration suppression are documented in the paper. Another contact modelling approach intended for more complex contact surfaces is based on the decomposition of a contact surface into a set of elementary areas and on the expression of contact and friction forces between these areas. All methodologies are implemented in the MATLAB system and the results for the chosen test cases are compared with the results obtained by a measurement or by the ANSYS software.
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Gonchikar, Ugrasen, Holalu Venkatadasu Ravindra, Prathik Jain Sudhir, Umeshgowda Bettahally Mahadevegowda, and Shankarnarayan Maskibail Suresh. "Estimation and Comparison of Welding Responses Using MRA, GMDH and ANN Technique of Al6061 and Al7075 Material in FSW." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11168.

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Abstract Friction Stir Welding (FSW) is a solid state welding which uses non-consumable steel rod to weld two materials. Friction stir welding is an emerging process which is based on frictional heat generated through contact between a non-consumable rotating tool and work piece. Friction stir welding technique possesses several advantages over other conventional types of welding due to the fact that process is carried out in solid state. Removal of melting helps in minimizing porosity and eliminates oxide inclusion. In this study, we focus on the optimization of the process parameters in friction stir welding of two different aluminium alloys (6061, 7075) using Taguchi method of experimental design. Al 6061 and Al 7075 are the two different alloys of aluminium. Among these Al 7075 has mechanical properties nearly double than that of Al 6061, but Al 6061 is used more extensively than Al 7075 because of its low cost. Al 6061 and Al 7075 being alloys of aluminium varies in the composition of alloying elements used in their manufacturing. Al 6061 has magnesium and silicon as its major alloying elements whereas Al 7075 has zinc as its primary alloying element. Al 6061 comes with medium to high strength, exhibit good toughness and surface finish, excellent resistance to corrosion at environmental conditions and another important property is its good weldability. Al 7075 being stronger than Al 6061 lacks in its resistance to corrosion and has poor weldability. Al 6061 is readily weldable but Al 7075 is not, because it is prone to micro-cracking during welding. This study also describes the relation between process parameters and their response of friction stir weld on ultimate tensile strength and hardness of composite materials using mathematical models. The process parameters considered are rotational speed, welding speed and number of passes. Different methodologies are used to develop the models to predict the responses and mechanical properties such as ultimate tensile strength and hardness. The objective of Multiple Regression Analysis (MRA) is to construct a model that explains as much as possible, the variability in a dependent variable, using several independent variables. Group Method of data Handling Technique (GMDH) is a family of inductive algorithms for computer-based mathematical modelling of multi-parametric datasets that features fully automatic structural and parametric optimization of models. GMDH is used in such fields as data mining, knowledge discovery, prediction, complex systems modelling, optimization and pattern recognition. As the machining process is non-linear and time dependent, it is difficult for the traditional identification methods to provide an accurate model. Compared to traditional computing methods, the Artificial Neural Network’s (ANN) are robust and global. Estimation and comparison of machining responses were carried out by MRA, GMDH and ANN.
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Eleye-Datubo, A. G., H. S. Sii, J. Wang, J. B. Yang, and J. Liu. "The Application of Approximate Reasoning Methodologies to Offshore Engineering Design Based on Risk Assessment." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58244.

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In dealing with complex and ill-defined systems of an offshore application, modelling of human reasoning for the purpose of risk assessment requires the effectiveness of a systematic logic-based approach. Floating production, storage and offloading (FPSO) installations, for example, combine traditional process technology with marine technology, and thus are quite dependent on technical design and operational safety control. Such safety-critical dependencies require novel approaches to properly analyse the risk involved. Hence, a proposed framework utilising approximate reasoning and evidential reasoning approaches is provided for modelling the assessment task. As based on fuzzy set theory, the model enables uncertainties to be described mathematically and further processed in the analysis of the structures. The forms of membership functions that could be used in representing fuzzy linguistic variables to quantify risk levels are presented. A case study of collision risk between FPSO and shuttle tanker due to technical failure during tandem offloading operation is used in this paper to illustrate the application of the proposed model. Furthermore, the obtained results from the case study provide confirmation that at various stages of offshore engineering systems design process the framework of incorporated approximate reasoning is a suited and convenient tool for attaining reliable risk analysis.
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Vogrinec, Monika, and Drago Bokal. "Doseganje višjih kognitivnih ciljev z vključevanjem hackathona v učni proces." In Values, Competencies and Changes in Organizations. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-442-2.75.

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With the lack of time and abundance of distractions, to which we are subject to when lecturing and assimilating new knowledge, it is very important to form lecturing processes that allow management of compromises between the learning experiences, goal depth, range of the used concepts, and effective feedback about correct understanding of learned material. In this paper, we present a hackathon concept with outcome directed to specific applicable results. Besides higher efficiency at achieving the goals, the learning process is monitored using a questionnaire, which induces reflection on comprehension of learned concepts. Because of a large amount of autonomous and focused work, the mentee solves the problem with greater quality and uses the questionnaire for recieving feedback as a substitute to grade. In this way, the self-evaluation helps the mentor to indentify the weaknesses of understaning, while simultaneously the examination of self- evaluation with the mentor is the foundation of mentees self- criticism and becomes the tool in formative monitoring regarding assimilation of new knowledge. The hackathon concept is adapted to learning by a reflection of progress in project execution and understanding of the concepts learned along the way at a course on Combinatorial optimization. It is also appropriate for other courses that lecture quantitative methodologies (Mathematican modelling, Operating research, Statistics, subjects of programing and data analytics). The result is a learning process, adapted to the mentee, where the lecturer takes on the role of a mentor. With his in-depth knowledge of the topic, the mentor guides the mentee at searching for solutions of the problem and simultaneously through observation of the mentee adjusts the depth and contents to outset of the mentee and his ability to acquire knowledge.
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Cunha, Sérgio B., and Renan M. Baptista. "Pipeline Leak Detection Using a Moderate Gain Nonlinear Observer." In 2020 13th International Pipeline Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipc2020-9333.

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Abstract:
Abstract Most pipeline control systems use some sort of autonomous leak detection system as a safety feature. Among the pipeline leak detection techniques, state observers stand out as the most sophisticated and promising technique. But its use has been inhibited as the dynamic models employed so far are large and estimating the states of nonlinear systems is not trivial. Pipeline pressure and flow dynamics have been modelled in the literature by means of different numerical solutions to a pair of first order partial differential equations that express mass and linear momentum conservation. The numerical solution requires discretizing the pipeline length in a finite number of segments, resulting in a system of equations with size of twice the number of segments. Although there is nothing wrong with this approach, a smaller system is more convenient if one is concerned exclusively with pressure and flow at the pipeline entrance and exit sections. In this paper, energetic modelling principles are employed to obtain a pair of first order ordinary differential equations representing the dynamics of long liquid pipelines. A recently introduced nonlinear observer enables straightforward use of linear, constant-gain observers with Lipschitz nonlinear dynamics. This observer gives the designer freedom to choose the observer eigenvalues and enables mathematically proven asymptotic stability with low gains. In this paper this observer, using a second-order model to represent the pipeline dynamics, is used as a pipeline leak detection algorithm. Initially the observer was employed directly as a leak detection algorithm, the leak being indicated by a non-transient difference between the measured and the estimated flows. Afterwards the leak was modeled as a disturbance flow and a disturbance observer was designed. Both algorithms were verified by means of computer simulations. It was found that the two methodologies are capable of detecting and estimating very small leaks, but the disturbance observer seems capable of indicating small holes further way from the measuring points.
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