EAGER: SSDIM: Data Generation for the Coupled System Composed of the Beef Cattle Production Infrastructure and the Transportation Services Infrastructure in Southwestern Kansas

EAGER：SSDIM：堪萨斯州西南部肉牛生产基础设施和运输服务基础设施组成的耦合系统的数据生成

• 批准号: 1744812
• 负责人: Caterina Scoglio
• 金额: $ 17.41万
• 依托单位: Kansas State University
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744812&HistoricalAwards=false
• 关键词: EAGER; SSDIM; Data; Generation; Coupled

This EArly-concept Grant for Exploratory Research (EAGER) project will generate simulated data to model the behaviors of the interdependent beef production system and transportation infrastructure in southwestern Kansas, with due consideration of key social and economic factors. This process involves: i) modeling of the system as a multilayer network; ii) designing of an agent-based model incorporating all collected data and considering key social and economic aspects; iii) assessment of interdependencies between the beef production and transportation infrastructures, iv) evaluation of different scenarios and their impact on the infrastructure performance. The generated data will be organized and publicly shared with the final goal of increasing the understanding of these coupled systems. Benefits of this work include improved understanding of how to prevent and contain risks to these systems, thus contributing to the goal of greater safety and economic viability. Mentoring and training of a graduate student in the conduct of interdisciplinary research is an important component of the research. Project data and software will be publicly shared through websites and results disseminated through academic conferences and journals. The Center for Engagement and Community Development of Kansas State University will be utilized to distribute project results to target stakeholder audiences through the organization of a workshop in a critical location for the beef industry.From a theoretical perspective, the expected outcomes will provide novel insights into the structural characteristics and the interdependencies of coupled infrastructures. New methods and models will be developed and made publicly available for scientists in the field to use in other regions and other contexts. From an application perspective, the data generated in this project will advance current knowledge of the beef production and transportation systems. Furthermore, the significant economic and social aspects of these interdependent systems will provide foundational elements for cross-disciplinary analysis in the domains of network science and social organization.

这个早期概念探索性研究补助金(AGER)项目将生成模拟数据，以模拟堪萨斯州西南部相互依存的牛肉生产系统和交通基础设施的行为，并适当考虑关键的社会和经济因素。这一过程包括：i)将系统建模为多层网络；ii)设计基于代理的模型，纳入所有收集的数据，并考虑关键的社会和经济方面；iii)评估牛肉生产和运输基础设施之间的相互依存关系；iv)评估不同情景及其对基础设施性能的影响。生成的数据将被组织起来并公开分享，最终目标是增加对这些耦合系统的了解。这项工作的好处包括更好地了解如何预防和控制这些系统的风险，从而有助于实现更大的安全性和经济可行性的目标。对研究生进行跨学科研究的指导和培训是这项研究的重要组成部分。项目数据和软件将通过网站公开分享，并通过学术会议和期刊传播成果。堪萨斯州立大学参与和社区发展中心将通过在牛肉行业的关键地点组织研讨会，将项目成果分发给目标利益相关者受众。从理论角度来看，预期结果将为耦合基础设施的结构特征和相互依赖提供新的见解。将开发新的方法和模型，并将其公之于众，供该领域的科学家在其他区域和其他背景下使用。从应用的角度来看，该项目中产生的数据将促进当前对牛肉生产和运输系统的了解。此外，这些相互依存的系统的重大经济和社会方面将为网络科学和社会组织领域的跨学科分析提供基本要素。

项目成果

A Permissioned Distributed Ledger for the US Beef Cattle Supply Chain

• DOI: 10.1109/access.2020.3019000
• 发表时间: 2020
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Tanvir Ferdousi;D. Gruenbacher;C. Scoglio

Robustness of supply chain networks against underload cascading failures

• DOI: 10.1016/j.physa.2020.125466
• 发表时间: 2021-02-01
• 期刊: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
• 影响因子: 3.3
• 作者: Yang, Qihui;Scoglio, Caterina M.;Gruenbacher, Don M.
• 通讯作者: Gruenbacher, Don M.

Developing an agent-based model to simulate the beef cattle production and transportation in southwest Kansas

• DOI: 10.1016/j.physa.2019.04.092
• 发表时间: 2019-07
• 期刊: Physica A: Statistical Mechanics and its Applications
• 作者: Qihui Yang;D. Gruenbacher;Jessica L. Heier Stamm;Gary L. Brase;S. DeLoach;D. Amrine;C. Scoglio