726 research outputs found

    Meso-scale modeling of reaction-diffusion processes using cellular automata

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    Comparative analysis of asynchronous cellular automata in stochastic pharmaceutical modelling

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    In pharmaceutical modelling, cellular automata have been used as an established tool to represent molecular changes through discrete structural interactions. The data quality provided by such modelling is found suitable for the early drug design phase where flexibility is paramount. While both synchronous (CA) and asynchronous (ACA) types of automata have been used, analysis of their nature and comparative influence on model outputs is lacking. In this paper, we outline a representative probabilistic CA for modelling complex controlled drug formulations and investigate its transition from synchronous to asynchronous update algorithms. The key investigation points include quantification of model dynamics through three distinct scenarios, parallelisation performance and the ability to describe different release phenomena, namely erosion, diffusion and swelling. The choice of the appropriate update mechanism impacts the perceived realism of the simulation as well as the applicability of large-scale simulations

    Cellular-automata models of natural processes, implementation on supercomputers

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    Представлены результаты анализа моделирующих способностей и вычислительных свойств методов клеточно-автоматного (КА) моделирования нелинейных пространственно распределенных процессов. Работа преследует две цели: 1) показать соответствие свойств КА-моделей современным тенденциям развития параллельных многопроцессорных архитектур (дискретность представления данных, локальность взаимодействий) и 2) раскрыть возможности КА-методов для компьютерного моделирования естественных существенно нелинейных, диссипативных процессов, не поддающихся традиционным методам математического моделирования. Обобщается опыт КА-моделирования, полученный в ИВМиМГ СО РАН. Работа содержит формальное представление КА-моделей, методы их построения, а также результаты реализации ряда тестовых и реальных задач на суперкомпьютерах

    A Language-centered Approach to support environmental modeling with Cellular Automata

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    Die Anwendung von Methodiken und Technologien aus dem Bereich der Softwaretechnik auf den Bereich der Umweltmodellierung ist eine gemeinhin akzeptierte Vorgehensweise. Im Rahmen der "modellgetriebenen Entwicklung"(MDE, model-driven engineering) werden Technologien entwickelt, die darauf abzielen, Softwaresysteme vorwiegend auf Basis von im Vergleich zu Programmquelltexten relativ abstrakten Modellen zu entwickeln. Ein wesentlicher Bestandteil von MDE sind Techniken zur effizienten Entwicklung von "domänenspezifischen Sprachen"( DSL, domain-specific language), die auf Sprachmetamodellen beruhen. Die vorliegende Arbeit zeigt, wie modellgetriebene Entwicklung, und insbesondere die metamodellbasierte Beschreibung von DSLs, darüber hinaus Aspekte der Pragmatik unterstützen kann, deren Relevanz im erkenntnistheoretischen und kognitiven Hintergrund wissenschaftlichen Forschens begründet wird. Hierzu wird vor dem Hintergrund der Erkenntnisse des "modellbasierten Forschens"(model-based science und model-based reasoning) gezeigt, wie insbesondere durch Metamodelle beschriebene DSLs Möglichkeiten bieten, entsprechende pragmatische Aspekte besonders zu berücksichtigen, indem sie als Werkzeug zur Erkenntnisgewinnung aufgefasst werden. Dies ist v.a. im Kontext großer Unsicherheiten, wie sie für weite Teile der Umweltmodellierung charakterisierend sind, von grundsätzlicher Bedeutung. Die Formulierung eines sprachzentrierten Ansatzes (LCA, language-centered approach) für die Werkzeugunterstützung konkretisiert die genannten Aspekte und bildet die Basis für eine beispielhafte Implementierung eines Werkzeuges mit einer DSL für die Beschreibung von Zellulären Automaten (ZA) für die Umweltmodellierung. Anwendungsfälle belegen die Verwendbarkeit von ECAL und der entsprechenden metamodellbasierten Werkzeugimplementierung.The application of methods and technologies of software engineering to environmental modeling and simulation (EMS) is common, since both areas share basic issues of software development and digital simulation. Recent developments within the context of "Model-driven Engineering" (MDE) aim at supporting the development of software systems at the base of relatively abstract models as opposed to programming language code. A basic ingredient of MDE is the development of methods that allow the efficient development of "domain-specific languages" (DSL), in particular at the base of language metamodels. This thesis shows how MDE and language metamodeling in particular, may support pragmatic aspects that reflect epistemic and cognitive aspects of scientific investigations. For this, DSLs and language metamodeling in particular are set into the context of "model-based science" and "model-based reasoning". It is shown that the specific properties of metamodel-based DSLs may be used to support those properties, in particular transparency, which are of particular relevance against the background of uncertainty, that is a characterizing property of EMS. The findings are the base for the formulation of an corresponding specific metamodel- based approach for the provision of modeling tools for EMS (Language-centered Approach, LCA), which has been implemented (modeling tool ECA-EMS), including a new DSL for CA modeling for EMS (ECAL). At the base of this implementation, the applicability of this approach is shown

    Vormen van inzicht

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    Stochastic computational modelling of complex drug delivery systems

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    As modern drug formulations become more advanced, pharmaceutical companies face the need for adequate tools to permit them to model complex requirements and to reduce unnecessary adsorption rates while increasing the dosage administered. The aim of the research presented here is the development and application of a general stochastic framework with agent-based elements for building drug dissolution models, with a particular focus on controlled release systems. The utilisation of three dimensional Cellular Automata and Monte Carlo methods, to describe structural compositions and the main physico-chemical mechanisms, is shown to have several key advantages: (i) the bottom up approach simplifies the definition of complex interactions between underlying phenomena such as diffusion,polymer degradation and hydration, and the dissolution media; (ii) permits straightforward extensibility for drug formulation variations in terms of supporting various geometries and exploring effects of polymer composition and layering; (iii) facilitates visualisation, affording insight on system structural evolution over time by capturing successive stages of dissolution. The framework has been used to build models simulating several distinct release scenarios from coated spheres covering single coated erosion and swelling dominated spheres as well as the influence of multiple heterogeneous coatings. High-performance computational optimisation enables precision simulations of the very thin coatings used and allows fast realisation of model state changes. Furthermore, theoretical analysis of the comparative impact of synchronous and asynchronous Cellular Automata and the suitability of their application to pharmaceutical systems is performed. Likely parameter distributions from noisy in vitro data are reconstructed using Inverse Monte Carlo methods and outcomes are reported

    Common metrics for cellular automata models of complex systems

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    The creation and use of models is critical not only to the scientific process, but also to life in general. Selected features of a system are abstracted into a model that can then be used to gain knowledge of the workings of the observed system and even anticipate its future behaviour. A key feature of the modelling process is the identification of commonality. This allows previous experience of one model to be used in a new or unfamiliar situation. This recognition of commonality between models allows standards to be formed, especially in areas such as measurement. How everyday physical objects are measured is built on an ingrained acceptance of their underlying commonality. Complex systems, often with their layers of interwoven interactions, are harder to model and, therefore, to measure and predict. Indeed, the inability to compute and model a complex system, except at a localised and temporal level, can be seen as one of its defining attributes. The establishing of commonality between complex systems provides the opportunity to find common metrics. This work looks at two dimensional cellular automata, which are widely used as a simple modelling tool for a variety of systems. This has led to a very diverse range of systems using a common modelling environment based on a lattice of cells. This provides a possible common link between systems using cellular automata that could be exploited to find a common metric that provided information on a diverse range of systems. An enhancement of a categorisation of cellular automata model types used for biological studies is proposed and expanded to include other disciplines. The thesis outlines a new metric, the C-Value, created by the author. This metric, based on the connectedness of the active elements on the cellular automata grid, is then tested with three models built to represent three of the four categories of cellular automata model types. The results show that the new C-Value provides a good indicator of the gathering of active cells on a grid into a single, compact cluster and of indicating, when correlated with the mean density of active cells on the lattice, that their distribution is random. This provides a range to define the disordered and ordered state of a grid. The use of the C-Value in a localised context shows potential for identifying patterns of clusters on the grid
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