Excellence in Research: A Spatiotemporal Sustainability Method for Post-Disaster Vegetative Debris Management

卓越研究:灾后植被碎片管理的时空可持续性方法

基本信息

项目摘要

Storms generate large volumes of vegetative debris, which often require significant resources for timely collection and disposal. This abundant debris also holds great potential for recycling and reuse, diverting it from landfills and creating value in end-of-life materials. However, it is critical to collect and process the debris promptly (before significant decomposition occurs) to maximize its value. Unfortunately, current debris management practices overlook the varying material conditions of vegetative debris in different storm-affected areas, limiting the sustainable use of these valuable resources. To address these challenges, the Principal Investigators (PIs) of this this Excellence in Research (EiR) project propose to study and understand the changing organic conditions of storm vegetative debris over time and space and integrate this knowledge into a data-driven planning framework for post-storm debris management. By considering the evolving condition of vegetative debris across storm-affected areas, the proposed planning method will optimize debris collection resource allocation to enhance recycling and reuse of collected materials. The successful completion of this project will benefit society through the potential improvement of post-disaster debris planning, waste reduction, and the creation of valuable end-of-life materials. Additional benefits to society will be achieved through student education and training including the mentoring of two graduate students as well as mentoring of a post-doctoral scholar at Florida Agricultural and Mechanical University (FAMU) and mentoring of a graduate student at California Polytechnic State University.Large quantities of vegetative debris require significant resources for timely management. Vegetative holds substantial potential for recycling and reuse, reducing landfill waste and creating value in end-of-life materials. However, the decomposition of organic materials poses challenges to achieving sustainable utilization. Given the spatial variability due to storage conditions and geographic distribution, as well as the temporal changes during collection, temporary storage, and final use or disposal, it is crucial to consider both spatial and temporal aspects in informed sustainable disaster waste management planning. To address this challenge, the Principal Investigators (PIs) of this project propose to investigate and unravel the characteristics and evolution of storm-related vegetative debris in space and time, integrating this understanding into data-driven debris management planning to enhance recycling, reuse, and advance sustainable waste management practices. The specific research objectives are to 1) identify the temporal evolution of vegetative debris and model the dynamic decomposition potential of uncollected debris; 2) develop an agent-based modeling (ABM) simulation model of debris collection operations and compare the spatially extended temporal performance-driven approach with the temporal-only approach using the simulation model and material assessment model; and 3) develop a novel spatial-temporal sustainability-based planning methodology for debris recovery. The successful completion of this project could lead to a paradigm shift in post-disaster planning, transitioning from the conventional time-based framework to a novel extended time- and space-based framework to enable more effective and sustainable debris management. To implement the education and training goals of the project, the PIs plan to engage with the Educating Engineering Students Innovatively (EESI) program at FAMU to enhance learning of students underrepresented in STEM. In addition, the PIs plan to engage with local agencies and contractors to make research products more relevant to management practicesThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
风暴产生大量植物残骸,往往需要大量资源及时收集和处理。这些丰富的废弃物也具有回收和再利用的巨大潜力,将其从垃圾填埋场转移出来,并为报废材料创造价值。然而,必须及时收集和处理碎片(在发生重大分解之前),以最大限度地发挥其价值。不幸的是,目前的碎片管理做法忽视了不同风暴影响地区植物碎片的不同物质条件,限制了这些宝贵资源的可持续利用。为了应对这些挑战,本卓越研究(EiR)项目的主要研究人员(PI)建议研究和了解风暴植被碎片随时间和空间变化的有机条件,并将这些知识整合到风暴后碎片管理的数据驱动规划框架中。通过考虑受风暴影响地区植物碎片的演变情况,拟议的规划方法将优化碎片收集资源分配,以加强回收和再利用收集的材料。该项目的成功完成将通过改善灾后碎片规划、减少废物和创造有价值的报废材料而造福社会。还将通过学生教育和培训为社会带来更多好处,包括指导佛罗里达农业和机械大学的两名研究生和一名博士后学者,指导加州理工州立大学的一名研究生。Vegetative在回收和再利用方面具有巨大的潜力,可减少垃圾填埋废物,并为报废材料创造价值。然而,有机材料的分解对实现可持续利用提出了挑战。鉴于储存条件和地理分布造成的空间变异性,以及收集、临时储存和最终使用或处置期间的时间变化,在知情的可持续灾害废物管理规划中必须考虑空间和时间两个方面。为了应对这一挑战,该项目的首席研究员(PI)建议调查和揭示与风暴有关的植物碎片在空间和时间上的特征和演变,将这种理解纳入数据驱动的碎片管理规划,以加强回收,再利用和推进可持续废物管理实践。具体的研究目标是:1)确定植物残体的时间演变,模拟未收集残体的动态分解潜力; 2)建立残体收集作业的基于Agent的建模(ABM)仿真模型,并利用仿真模型和材料评估模型比较空间扩展的时间性能驱动方法和仅时间方法;(3)为碎片回收制定一种新的基于时空可持续性的规划方法。该项目的成功完成可能导致灾后规划的范式转变,从传统的基于时间的框架过渡到新的扩展的基于时间和空间的框架,以实现更有效和可持续的碎片管理。为了实现该项目的教育和培训目标,PI计划与FAMU的创新教育工程学生(EESI)计划合作,以加强STEM中代表性不足的学生的学习。此外,PI计划与当地机构和承包商合作,使研究产品与管理实践更加相关。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Juyeong Choi其他文献

Exploratory Framework for Application of Analytics in the Construction Industry
建筑行业分析应用探索性框架
  • DOI:
    10.1061/(asce)me.1943-5479.0000409
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Nader Naderpajouh;Juyeong Choi;M. Hastak
  • 通讯作者:
    M. Hastak
Reuse and Recycling Feasibility Assessment for Bridge Components: A Case Study of a Bridge Investigation in Florida
桥梁构件的再利用和回收可行性评估:佛罗里达州一座桥梁调查的案例研究
Transportation system performance capabilities for vulnerable populations
针对弱势群体的交通系统性能能力
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Mazin AbdelMagid;Y. AbdelRazig;Dennis Smith;Mark W. Horner;Juyeong Choi;Kyusik Kim;Billie Ventimiglia
  • 通讯作者:
    Billie Ventimiglia
Dynamics of project selection and growth in project-based organizations
基于项目的组织中项目选择和成长的动态

Juyeong Choi的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Juyeong Choi', 18)}}的其他基金

Planning: Establishing an Industry Partnership for Sustainable Demolition Research on Climate Change
规划:建立行业合作伙伴关系,开展气候变化可持续拆除研究
  • 批准号:
    2331975
  • 财政年份:
    2023
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
CAREER: Sustainable Material Harvesting in Civil Engineering: A Building Lifecycle Approach to Maximize Recyclable and Reusable Demolition Waste
职业:土木工程中的可持续材料收获:最大化可回收和可再利用拆除废物的建筑生命周期方法
  • 批准号:
    2238612
  • 财政年份:
    2023
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Continuing Grant
RAPID: Investigating Illegal Dumping During the Course of Debris Collection Operations Following Hurricane Ian
RAPID:调查伊恩飓风后碎片收集作业过程中的非法倾倒行为
  • 批准号:
    2305113
  • 财政年份:
    2022
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
RAPID: The Impact of the Coronavirus (COVID-19) Pandemic on Municipal Solid Waste Management Systems
RAPID:冠状病毒(COVID-19)大流行对城市固体废物管理系统的影响
  • 批准号:
    2030254
  • 财政年份:
    2020
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
EAGER: SUstainable Material Management Extreme Events Reconnaissance (SUMMEER) Organization
EAGER:可持续材料管理极端事件侦察 (SUMMEER) 组织
  • 批准号:
    2014330
  • 财政年份:
    2020
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Planning: FIRE-PLAN:High-Spatiotemporal-Resolution Sensing and Digital Twin to Advance Wildland Fire Science
合作研究:规划:FIRE-PLAN:高时空分辨率传感和数字孪生,以推进荒地火灾科学
  • 批准号:
    2335568
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Planning: FIRE-PLAN:High-Spatiotemporal-Resolution Sensing and Digital Twin to Advance Wildland Fire Science
合作研究:规划:FIRE-PLAN:高时空分辨率传感和数字孪生,以推进荒地火灾科学
  • 批准号:
    2335569
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Understanding the Influence of Turbulent Processes on the Spatiotemporal Variability of Downslope Winds in Coastal Environments
合作研究:了解湍流过程对沿海环境下坡风时空变化的影响
  • 批准号:
    2331729
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Continuing Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
  • 批准号:
    2403312
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Planning: FIRE-PLAN:High-Spatiotemporal-Resolution Sensing and Digital Twin to Advance Wildland Fire Science
合作研究:规划:FIRE-PLAN:高时空分辨率传感和数字孪生,以推进荒地火灾科学
  • 批准号:
    2335570
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: Learning AI Surrogate of Large-Scale Spatiotemporal Simulations for Coastal Circulation
合作研究:OAC Core:学习沿海环流大规模时空模拟的人工智能替代品
  • 批准号:
    2402947
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
  • 批准号:
    2403313
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Understanding the Influence of Turbulent Processes on the Spatiotemporal Variability of Downslope Winds in Coastal Environments
合作研究:了解湍流过程对沿海环境下坡风时空变化的影响
  • 批准号:
    2331728
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Continuing Grant
Collaborative Research: Urban Vector-Borne Disease Transmission Demands Advances in Spatiotemporal Statistical Inference
合作研究:城市媒介传播疾病传播需要时空统计推断的进步
  • 批准号:
    2414688
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Continuing Grant
Collaborative Research: OAC Core: Learning AI Surrogate of Large-Scale Spatiotemporal Simulations for Coastal Circulation
合作研究:OAC Core:学习沿海环流大规模时空模拟的人工智能替代品
  • 批准号:
    2402946
  • 财政年份:
    2024
  • 资助金额:
    $ 59.93万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了