Understanding structural health monitoring data to support decision-making processes and service life management of mass timber buildings. A preliminary study on use of data scaffolding

被引:1
|
作者
Riggio, Mariapaola [1 ,3 ]
Dilmaghani, Morvarid [1 ]
Sanchez, Christopher A. [2 ]
机构
[1] Oregon State Univ, Wood Sci & Engn Dept, Corvallis, OR USA
[2] Oregon State Univ, Sch Psychol Sci, Corvallis, OR USA
[3] Oregon State Univ, Wood Sci & Engn Dept, 119 Richardson Hall, Corvallis, OR 97331 USA
关键词
Timber buildings; decision making; SHM; sensor data; data sense-making; data scaffolding; hygrothermal monitoring; structural monitoring; GRAPH COMPREHENSION; MOISTURE-CONTENT; VISUALIZATION; INFORMATION; EXPERTS; MODEL; ENVIRONMENTS;
D O I
10.1080/20426445.2023.2177092
中图分类号
TB3 [工程材料学]; TS [轻工业、手工业、生活服务业];
学科分类号
0805 ; 080502 ; 0822 ;
摘要
Structural health monitoring (SHM) can be used to support decision-making processes leading to improved building management plans. With advanced engineered wooden buildings on the rise, SHM has emerged as a critical tool to document behaviour of these structures. However, monitoring data need to be easily accessible and understandable to support informed decisions. This study explores the potential benefits of an intentionally designed data scaffolding to support interpretation of SHM data for timber structures. Results suggest that appropriate scaffolding (e.g. pinpointing critical parameter ranges) can enable lay users to better interpret monitoring data of timber structures. Results also suggest that, for more highly educated users, access to graphs linked to metadata can be beneficial. Overall, it appears that documentation related to the monitored phenomena and context, as well as more explicit reference to building performance requirements, could improve data-driven decision making for all knowledge levels for the building maintenance sector.
引用
收藏
页码:42 / 59
页数:18
相关论文
共 6 条
  • [1] Leveraging Structural Health Monitoring Data Through Avatars to Extend the Service Life of Mass Timber Buildings
    Riggio, Mariapaola
    Mrissa, Michael
    Kresz, Miklos
    Vcelak, Jan
    Sandak, Jakub
    Sandak, Anna
    FRONTIERS IN BUILT ENVIRONMENT, 2022, 8
  • [2] Bayesian Decision-Making Process Including Structural Health Monitoring Data Quality for Bridge Management
    Makhoul, Nisrine
    KSCE JOURNAL OF CIVIL ENGINEERING, 2024, 28 (07) : 2818 - 2835
  • [3] Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study
    Hinrichs, Maren
    Prifti, Loina
    Schneegass, Stefan
    JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING, 2024, 30 (01) : 202 - 220
  • [4] Clinician's perspective on trusting Patient Generated Health Data for use in clinical decision-making: A qualitative interview study.
    Hedennan, Lucy
    Berry, Damon
    Ormazabal, Alfredo
    2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS, 2023, : 252 - 256
  • [5] "There Is No Link Between Resource Allocation and Use of Local Data": A Qualitative Study of District-Based Health Decision-Making in West Bengal, India
    Bhattacharyya, Sanghita
    Issac, Anns
    Girase, Bhushan
    Guha, Mayukhmala
    Schellenberg, Joanna
    Avan, Bilal Iqbal
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (21) : 1 - 15
  • [6] Electronic medical record systems data use in decision-making and associated factors among health managers at public primary health facilities, Dodoma region: a cross-sectional analytical study
    Kessy, Eusebi Cornelius
    Kibusi, Stephen Mathew
    Ntwenya, Julius Edward
    FRONTIERS IN DIGITAL HEALTH, 2024, 5