EAGER: SSDIM: Superimposed Simulations: Fast Generation of Synthetic Data of Interdependent Critical Infrastructures

EAGER：SSDIM：叠加模拟：快速生成相互依赖的关键基础设施的综合数据

• 批准号: 1745580
• 负责人: John Crittenden
• 金额: $ 15万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1745580&HistoricalAwards=false
• 关键词: EAGER; SSDIM; Superimposed; Simulations; Fast

To guide the design, construction, operation and improved understanding of modern interdependent critical infrastructure (ICI) systems, decision-makers require data that capture the interactions among them their actors (i.e., citizens, firms, developers, and governments). Detailed computer simulations are essential to generating such data, particularly when physical implementations of ICI designs do not yet exist. However, generation of data derived from simulations is time consuming due to the complexity of the systems that must be modeled and the large number of computational experiments that are required. To address this challenge new computer algorithms exploiting modern high performance computing technologies will be developed. In this EArly-concept Grant for Exploratory Research (EAGER) project, algorithms will be applied to create data sets for test cases including the interaction of water, energy, transportation infrastructures and people in the city of Atlanta. The new algorithms will provide insights into how to evaluate threats and opportunities within and across ICIs, to analyze strengths and weaknesses, and to design solutions, products, and services that meet societal needs and goals.Current computational methods to assess options, various technology combinations, and human interactions within ICIs are time-consuming and computationally intensive. A new approach, termed superimposed simulations, will be developed to rapidly create synthetic data that captures the interdependencies and dynamics of critical infrastructures and people. By exploiting similarities among the many simulation runs in conjunction with parallel computing techniques, the new algorithms aim to accelerate simulations involving multiple interacting and interdependent critical infrastructure systems and human actors by one or two orders of magnitude. These newly developed algorithms will allow the quick generation of large data sets that can be used to determine the effects of ICI combinations, human behaviors, and policy tools on energy, water, carbon emissions, and human health.

为了指导现代相互依赖的关键基础设施(ICI)系统的设计、建设、运营和更好的理解，决策者需要数据来捕捉他们的参与者(即公民、公司、开发人员和政府)之间的互动。详细的计算机模拟对于生成此类数据至关重要，尤其是在ICI设计的物理实现尚不存在的情况下。然而，由于必须建模的系统的复杂性和所需的大量计算实验，从仿真中产生的数据是耗时的。为了应对这一挑战，将开发利用现代高性能计算技术的新计算机算法。在这个探索性研究早期概念拨款(AGER)项目中，算法将被应用于创建测试用例的数据集，包括亚特兰大市水、能源、交通基础设施和人的相互作用。新的算法将为如何评估ICIS内部和整个ICIS内的威胁和机会，分析优势和劣势，以及设计满足社会需求和目标的解决方案、产品和服务提供见解。目前评估ICIS内的选项、各种技术组合和人类交互的当前计算方法既耗时又计算密集。将开发一种名为叠加模拟的新方法，以快速创建合成数据，捕捉关键基础设施和人员的相互依存关系和动态。通过结合并行计算技术利用许多模拟运行之间的相似性，新算法的目标是将涉及多个相互作用和相互依赖的关键基础设施系统和人类参与者的模拟加速一到两个数量级。这些新开发的算法将允许快速生成大型数据集，这些数据集可用于确定ICI组合、人类行为和政策工具对能源、水、碳排放和人类健康的影响。

项目成果

Energy Efficient Middleware for Dynamic Data Driven Application Systems

用于动态数据驱动应用系统的节能中间件

• 发表时间: 2018
• 期刊: Winter Simulation Conference
• 作者: Biswas, A.;Hunter, M.;Fujimoto, R. M.
• 通讯作者: Fujimoto, R. M.

Toward a Common Object Model for Integrated Transportation and Land Use Models

建立综合交通和土地利用模型的通用对象模型

• 发表时间: 2018
• 期刊: Annual Simulation Symposium
• 作者: Robinson, C.;Crittenden, J.;Lu, Z.;Fujimoto, R. M.
• 通讯作者: Fujimoto, R. M.

Parametric life cycle assessment for distributed combined cooling, heating and power integrated with solar energy and energy storage

• DOI: 10.1016/j.jclepro.2019.119483
• 发表时间: 2020-03
• 期刊: Journal of Cleaner Production
• 影响因子: 11.1
• 作者: Junchen Yan;Osvaldo A. Broesicke;Dong Wang;Duo Li;J. Crittenden

Granular Cloning: Intra-Object Parallelism in Ensemble Studies

粒度克隆：集成研究中的对象内并行性

• DOI: 10.1145/3200921.3200927
• 发表时间: 2018
• 期刊: SIGSIM-PADS '18: Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
• 作者: Pecher, Philip;Crittenden, John;Lu, Zhongming;Fujimoto, Richard
• 通讯作者: Fujimoto, Richard