227,814 research outputs found

    MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

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    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

    The role of learning on industrial simulation design and analysis

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    The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

    Ship product modelling

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    This paper is a fundamental review of ship product modeling techniques with a focus on determining the state of the art, to identify any shortcomings and propose future directions. The review addresses ship product data representations, product modeling techniques and integration issues, and life phase issues. The most significant development has been the construction of the ship Standard for the Exchange of Product Data (STEP) application protocols. However, difficulty has been observed with respect to the general uptake of the standards, in particular with the application to legacy systems, often resulting in embellishments to the standards and limiting the ability to further exchange the product data. The EXPRESS modeling language is increasingly being superseded by the extensible mark-up language (XML) as a method to map the STEP data, due to its wider support throughout the information technology industry and its more obvious structure and hierarchy. The associated XML files are, however, larger than those produced using the EXPRESS language and make further demands on the already considerable storage required for the ship product model. Seamless integration between legacy applications appears to be difficult to achieve using the current technologies, which often rely on manual interaction for the translation of files. The paper concludes with a discussion of future directions that aim to either solve or alleviate these issues

    Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm

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    Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved in the model integration process, discuss modelling and software development approaches, and present preliminary results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant reaction and transport in bed-sediments

    Distributed Simulation of Heterogeneous and Real-time Systems

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    This work describes a framework for distributed simulation of cyber-physical systems (CPS). Modern CPS comprise large numbers of heterogeneous components, typically designed in very different tools and languages that are not or not easily composeable. Evaluating such large systems requires tools that integrate all components in a systematic, well-defined manner. This work leverages existing frameworks to facilitate the integration offers validation by simulation. A framework for distributed simulation is the IEEE High-Level Architecture (HLA) compliant tool CERTI, which provides the infrastructure for co-simulation of models in various simulation environments as well as hardware components. We use CERTI in combination with Ptolemy II, an environment for modeling and simulating heterogeneous systems. In particular, we focus on models of a CPS, including the physical dynamics of a plant, the software that controls the plant, and the network that enables the communication between controllers. We describe the Ptolemy extensions for the interaction with HLA and demonstrate the approach on a flight control system simulation
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