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SBIR Phase II: Real-Time Decision Making Software for Wastewater Treatment Operators

SBIR Phase II: Real-Time Decision Making Software for Wastewater Treatment Operators
SBIR 第二阶段:污水处理运营商实时决策软件
批准号:
2025902
负责人:
Keaton Lesnik
金额:
$88.37万
依托单位:
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-08-15 至 2023-02-28
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中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the development of a real-time software for wastewater facilities to improve nutrient removal and recovery at reduced costs. The technology developed through this SBIR project will provide a proactive monitoring process that allows wastewater operators to observe and diagnose future process upsets, proactively mitigate underlying root causes, and prevent pollutant release without the use of expensive and environmentally damaging chemicals. Improvements in treatment effectiveness and reduction of operating and maintenance costs will limit the environmental impact of human activities, improve sustainability of wastewater treatment infrastructure, ensure public health, and reduce financial burdens associated with wastewater treatment. Following deployment individual facilities may see annual commercial savings upwards of $1.4 M per large facility from improved compliance and reduction in chemical costs in a wastewater services, a market opportunity estimated at upwards of $420 M in the United States. This project could lead to 35% improvement in regulatory compliance, 35% reduction in chemical treatment costs, and a guidance system for inexperienced operators in an industry expecting 50% of its operator workforce to retire over the next 5-10 years. In addition, the project will develop a game-based training program to train new operators in the skill sets to lead operation of sophisticated facilities. This SBIR Phase II project proposes to further the development of a software platform that uses available operational, biological, and meteorological data as inputs to deliver process forecasts and insights regarding biological phosphorus removal to operators. Machine-learning forecast models will be the basis of an attribution-based inference and decision-making system used for diagnosis and mitigation of upsets to the notoriously unstable biological phosphorus removal process. In this project, data systems of a full-scale wastewater facility will be synced with the software platform to deliver real-time results that will be evaluated over 12 months of pilot testing.This 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.
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SBIR Phase I: Real-Time Decision Making Software for Wastewater Treatment Operators
  • 批准号:
    1843020
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2019
  • 负责人:
    Keaton Lesnik
  • 依托单位:
国内基金
海外基金
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  • 批准号:
    24ZR1429700
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    YUICHIRO NAKAI
  • 依托单位:
ATLAS实验探测器Phase 2升级
  • 批准号:
    11961141014
  • 项目类别:
    国际(地区)合作与交流项目
  • 资助金额:
    3350万元
  • 批准年份:
    2019
  • 负责人:
    刘衍文
  • 依托单位:
地幔含水相Phase E的温度压力稳定区域与晶体结构研究
  • 批准号:
    41802035
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    12.0万元
  • 批准年份:
    2018
  • 负责人:
    张里
  • 依托单位:
基于数字增强干涉的Phase-OTDR高灵敏度定量测量技术研究