DDDAS-TMRP: DynaCode: A General DDDAS Framework with Coast and Environment Modeling Applications

DynaCode专注于路易斯安那州沿海地区生态和沿海建模方面丰富且非常紧迫的科学问题，将为新一代复杂的DDDAS应用程序创建强大、通用、现代化的网络基础设施，从而推动许多科学和工程领域的发展。我们将建立和集成良好的开发和广泛使用的计算基础设施和新兴的标准，包括Cactus，Triana和网格服务。通过使用非常强大的应用程序开发工具，已经证明了先进的DDDAS功能，我们能够集中精力开发特定的DDDAS算法和软件模块，不仅适用于生态和沿海建模，但许多其他应用程序。 该项目将解决NOAA特别感兴趣的科学问题，涉及耦合海洋环流，风暴潮和海湾波浪生成模型的情景，以及路易斯安那州密西西比河三角洲地区的生态，水动力和沉积物运输模型，并将开发基础设施和算法，使这些模型相互耦合，并与传感器，风，以及其他数据和数据库，以优化网格上复杂工作流的执行，根据当前条件调用适当的模型、网格和算法。输入数据和复杂工作流程的真实的耦合将允许，例如，在飓风接近海岸时动态调用更准确的模型和算法，选择适当的计算资源，将模型结果与实际观测结果进行比较，将淡水控制改道与风暴潮模型相结合，以减少飓风破坏和洪水，或指导未来传感器和水坝的放置。在这个沿海建模项目的过程中，我们将开发工具包，以促进DDDAS方案，通过启用功能，如包装遗留代码，集成框架支持高级代码，允许数据的动态组合，因为它变得可用，运行多尺度模拟，并适应当前条件，如有必要，通过动态重组。

Focusing on the rich and very urgent scientific problems of ecological and coastal modeling of Lousiana's coastal region, DynaCode will create a powerful, generic, modern cyberinfrastructure for a new generation of complex DDDAS applications that will advance many areas of science and engineering. We will build upon and integrate well developed and widely used computational infrastructures and emerging standards, including Cactus, Triana, and grid services. By using very powerful application development tools that have already demonstrated advanced DDDAS capabilities, we are able to concentrate efforts on developing specific DDDAS algorithms and software modules that will apply not only to ecological and coastal modeling, but many other applications. The project will address scientific problems of particular interest to NOAA, involving scenarios that couple ocean circulation, storm surge, and wave generation models for the Gulf, as well as ecological, hydrodynamic, and sediment transport models of the Mississippi River Delta region of Louisiana, and will develop infrastructure and algorithms that enable these models to be coupled, both to each other and to external inputs from sensors, wind, and other data, and databases to optimize execution of complex workflows on grids, invoking appropriate models, meshes, and algorithms, depending on current conditions. The real time coupling of input data and complex workflows will allow, for example, dynamically invoking more accurate models and algorithms as a hurricane approaches the coast, choosing appropriate computing resources, comparing model results with actual observations, coupling freshwater control diversions with storm surge models to reduce hurricane damage and flooding, or guiding placement of future sensors and dams. In the course of this coastal modeling project, we will develop toolkits to facilitate DDDAS scenarios by enabling functionalities such as wrapping legacy codes, integrating framework support for advanced codes that allow dynamic composition of data as it becomes available, running multi scale simulations, and adapting to current conditions by dynamically recomposing if necessary.