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PFI:AIR - TT: Real-Time Fatigue Life Prediction for Decision-making and Asset Management

PFI:AIR - TT：用于决策和资产管理的实时疲劳寿命预测

基本信息

批准号：
1640693
负责人：
Masoud Sanayei
金额：
$ 19.99万
依托单位：
Tufts University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-15 至 2021-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640693&HistoricalAwards=false
关键词：
PFI AIR TT Real Time

项目摘要

This PFI: AIR Technology Translation project from Tufts University focuses on a Fatigue Health Portal (FHP), for translation of an advanced technology for real-time fatigue life prediction of in-service bridge structures. This product would fill an existing need to monitor and assess the conditions of aging US infrastructures. No existing product on the market offers real-time continuous operational fatigue prognosis and remaining life predictions, thus creating a market niche for the FHP. Full development, licensing, and commercialization of the FHP is vital as the US infrastructure ages, deteriorates and is thus increasingly "load-posted" (not recommended for transportation of materials and goods using heavier trucks). Load posting of bridges has major societal and commercial impact on the US market and economy and results in enormous costs of maintenance, retrofit, and replacement of the US highway bridges. An intelligent decision-oriented methodology can exploit real-time measured data and analysis, resulting in a more effective use of such information for infrastructure health monitoring and management. It will support a paradigm shift in the fatigue assessment profession to enable a data-driven and decision-oriented tool that can evolve as more structural response data is collected.The target market for this methodology is bridge managers and owners concerned with limited service life due to fatigue of steel elements. The broader target market is any structural engineer interested in data-driven intelligent decision-making with respect to fatigue assessment of in-service structures, such as transmission towers or amusement park rides. Under this project, two full-scale bridges and one other structural type will be the case studies for validation of the proposed methodologies, allowing refinement of the analytical methods and experimental techniques to address challenges of commercialization. The project will result in a FHP prototype software package with proof-of-concept that meets the need for improved decision-making in infrastructure asset management. It will integrate structural health monitoring concepts, analytical fatigue life prediction, and advanced nonparametric statistical methods to enable real-time fatigue assessment and prognosis to be used for decision-making and asset management. This project addresses the following technology gaps for real-time decision-making: (1) efficient and reliable wireless sensors, data acquisition, cloud computing, and data communications, (2) nonparametric decision-oriented probabilistic operational methods for infrastructure fatigue assessments, and (3) prognosis and prediction of remaining infrastructure fatigue life. The FHP has the following unique features: variable fatigue stress ranges, operational measured strains, unknown vehicle information, hypothesis testing for damage assessment, and use of an alert system that improves system safety. These features provide the following advantages: real-time structural fatigue life assessment using real-time measured strains, and use of efficient computational methodologies, which are cost effective when compared to the leading competing products and technology in this market space. This research collaboration, which involves three departments (Civil Engineering, Computer Science, and Economics) at two universities (Tufts University and University of New Hampshire), will strive to include underrepresented groups at the graduate, undergraduate, and high school level (students and teachers). In addition, personnel involved in this project will receive innovation, entrepreneurship, and technology translation experiences through product development, proof of concept, capstone projects, and licensing process of the IP. The academic and industrial partners of this project are looking forward to working together to transform research discoveries into market-ready products.The lead institution is Tufts University with its departments of Civil and Environmental Engineering, Computer Science, and Economics. The primary subcontractor is the University of New Hampshire, with a current PFI BIC project, The Living Bridge: The Future of Smart, User-Centered Transportation Infrastructure, which will be used for proof of concept of the FHP. Primary industrial partner is Bridge Diagnostic Inc. (BDI) to transform research discoveries into market-ready products and contact with consumers of FHP. Broader context partners are Six Flags New England, New Hampshire Department of Transportation, and Massachusetts Department of Transportation.

塔夫茨大学的 PFI：AIR 技术翻译项目重点关注疲劳健康门户 (FHP)，用于翻译在役桥梁结构实时疲劳寿命预测的先进技术。该产品将满足监测和评估美国老化基础设施状况的现有需求。市场上现有的产品还没有提供实时连续操作疲劳预测和剩余寿命预测，因此为 FHP 创造了一个市场利基。随着美国基础设施老化、恶化，FHP 的全面开发、许可和商业化至关重要，因此越来越多地“装载”（不建议使用重型卡车运输材料和货物）。桥梁的荷载发布对美国市场和经济具有重大的社会和商业影响，并导致美国公路桥梁的维护、改造和更换的巨额成本。智能决策导向方法可以利用实时测量数据和分析，从而更有效地利用此类信息进行基础设施健康监测和管理。它将支持疲劳评估行业的范式转变，以实现数据驱动和决策导向的工具，该工具可以随着收集更多结构响应数据而不断发展。该方法的目标市场是桥梁管理者和业主，他们担心由于钢构件疲劳而导致使用寿命有限。更广泛的目标市场是对数据驱动的智能决策感兴趣的任何结构工程师，这些决策涉及在役结构（例如输电塔或游乐园游乐设施）的疲劳评估。在该项目下，两座全尺寸桥梁和另一种结构类型将作为验证所提出方法的案例研究，从而改进分析方法和实验技术以应对商业化的挑战。该项目将产生一个带有概念验证的 FHP 原型软件包，可满足改进基础设施资产管理决策的需求。它将集成结构健康监测概念、分析疲劳寿命预测和先进的非参数统计方法，使实时疲劳评估和预测能够用于决策和资产管理。该项目解决了实时决策的以下技术差距：（1）高效可靠的无线传感器、数据采集、云计算和数据通信，（2）用于基础设施疲劳评估的非参数决策导向概率操作方法，以及（3）剩余基础设施疲劳寿命的预测和预测。 FHP 具有以下独特功能：可变疲劳应力范围、操作测量应变、未知车辆信息、损坏评估假设检验以及使用可提高系统安全性的警报系统。这些功能具有以下优势：使用实时测量的应变进行实时结构疲劳寿命评估，并使用高效的计算方法，与该市场领域领先的竞争产品和技术相比，这些方法具有成本效益。这项研究合作涉及两所大学（塔夫茨大学和新罕布什尔大学）的三个系（土木工程、计算机科学和经济学），将努力将研究生、本科生和高中阶段（学生和教师）的代表性不足的群体纳入其中。此外，参与该项目的人员将通过产品开发、概念验证、顶点项目和知识产权许可流程获得创新、创业和技术转化经验。该项目的学术和工业合作伙伴期待共同努力，将研究发现转化为可投入市场的产品。牵头机构是塔夫茨大学，设有土木与环境工程、计算机科学和经济学系。主要分包商是新罕布什尔大学，目前有一个 PFI BIC 项目“The Living Bridge：以用户为中心的智能交通基础设施的未来”，该项目将用于 FHP 的概念验证。主要工业合作伙伴是 Bridge Diagnostic Inc. (BDI)，将研究发现转化为市场就绪的产品并与 FHP 的消费者建立联系。更广泛的合作伙伴包括新英格兰六旗游乐园、新罕布什尔州交通部和马萨诸塞州交通部。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

What rollercoasters can teach us about fatigue life of bridge connections

过山车可以让我们了解桥梁连接的疲劳寿命

DOI：
10.1007/978-3-030-47634-2_2
发表时间：
2020
期刊：
Dynamics of Civil Structures
影响因子：
0
作者：
Tchemodanova, Sofia Puerto;Sanayei, Masoud
通讯作者：
Sanayei, Masoud

State Estimation for Prediction of Fatigue Life for a Rollercoaster Connection Subjected to Operational Multiaxial Nonproportional Loading

运行多轴非比例载荷下过山车连接疲劳寿命预测的状态估计

DOI：
10.1061/(asce)st.1943-541x.0002961
发表时间：
2021
期刊：
Journal of Structural Engineering
影响因子：
4.1
作者：
Tchemodanova, Sofia Puerto;Tatsis, Konstantinos;Sanayei, Masoud;Chatzi, Eleni;Dertimanis, Vasilis
通讯作者：
Dertimanis, Vasilis

Multiaxial fatigue life assessment of a vertical-lift bridge connection using strain rosette data

使用应变花环数据评估垂直升降桥连接的多轴疲劳寿命