Development of Stop Criteria for Proof Loading

Lantsoght, Eva O. L.; Yang, Young-Tae; Tersteeg, R.H.D.; Veen, C. van der; Boer, A. de

doi:10.1201/9781315375175-148

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…At this point, the method does not involve pre-stressed concrete structures and is thus limited to non-prestressed steel reinforced concrete. Similarly, stop criteria related to brittle failures such as shear failure mechanisms are still under further development [23][24][25][26][27][28][29].…”

Section: Literature Reviewmentioning

confidence: 99%

Identification of Stop Criteria for Large-Scale Laboratory Slab Tests Using Digital Image Correlation and Acoustic Emission

et al. 2022

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Advanced monitoring methods are required to identify stop criteria in proof-load tests. In this study, the combined methodology of two-dimensional digital image correlation and acoustic emission is investigated for its applicability for future implementation in field tests. The two monitoring systems are deemed to provide valuable insight with external measurements from digital image correlation and internal measurements from acoustic emission. Two overturned T-section reinforced concrete slabs (0.37 × 1.7 × 8.4 m) tested under laboratory conditions are used for the assessment. The first slab test served as a preliminary test to enable sensor placement and creation of a relevant loading protocol. The main scientific results lead to a proposal for a test procedure using the combined methodology based on results, observations, and experiences from an individual stop criteria assessment for the two methods. The results include full-field plots, an investigation of the time of crack detection and monitoring of crack widths with digital image correlation, and a qualitative assessment of activity vs. load followed by a quantitative evaluation of calm ratios using acoustic emission. The individual results show that both digital image correlation and acoustic emission can identify damage occurrence earlier than other secondary methods. At crack detection (415 kN), crack widths were measured at widths between 0.078 mm to 0.125 mm and can be monitored until reaching the stop criterion at 463 kN (Eurocode SLS threshold of wmax = 0.2 mm). The acoustic emission results were limited by the pre-defined loading protocol and thus, only indicated that damage occurred sometime between 300 kN and 500 kN (pre-defined load levels). Therefore, the proposal for test procedure involves a methodology, where the loading protocol may be updated during testing based on monitoring results and thus provide even more valuable data.

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Section: Literature Reviewmentioning

confidence: 99%

Identification of Stop Criteria for Large-Scale Laboratory Slab Tests Using Digital Image Correlation and Acoustic Emission

et al. 2022

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“…While the significance has been long recognized (e.g., Lytton, 1987;Markow, 1991;Rajagopal & George, 1991), the modeling of maintenance effectiveness has been until now mainly limited in pavement research (e.g., Ouyang & Madanat 2004;Pantelias & Zhang, 2009). Outside of pavement management, maintenance effectiveness was often integrated into the partially observable Markov decision process (POMDP) models (Alinizzi et al, 2018;Memarzadeh & Pozzi, 2016;Osman, Atef, & Moselhi, 2012;Papakonstantinou, Andriotis, & Shinozuka, 2018;Pozzi, Memarzadeh, & Klima, 2017;Srinivasan & Parlikad, 2013;Thöns, 2018;Van Erp & Orcesi, 2018). However, these POMDP studies take an assumed maintenance effectiveness model with little empirical support, if any at all.…”

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confidence: 99%

Integrative modeling of performance deterioration and maintenance effectiveness for infrastructure assets with missing condition data

Lin

Yuan

Tovilla

2019

Computer aided Civil Eng

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Deterioration modeling is an important analytical component in infrastructure asset management. It concerns the prediction of performance and remaining service life of assets of different designs under omnifarious working environments. For long‐term prediction, it also requires to characterize maintenance effectiveness because maintenance activities do not necessarily bring an asset to a completely renewed status. Deterioration modeling research has for decades been largely focusing on the modeling of the natural deterioration process per se, whereas the modeling of maintenance effectiveness is only a recent focus of investigation, mainly in pavement research. In practice, the asset conditions immediately before and after a given maintenance treatment both are not often known. This has made the modeling of maintenance effectiveness and long‐term deterioration prediction a challenging task. To bridge the gap, this paper presents a novel approach that integrates the modeling of deterioration and maintenance effectiveness into one process. The natural deterioration of asset performance is modeled as a continuous‐time Markov chain, whereas the effectiveness of a maintenance measure is modeled as a discrete‐time Markov chain. To account for missing condition data before and after the maintenance event, the paper also develops a robust statistical method based on Markov chain Monte Carlo simulation. A real‐life case study on a municipal sewer pipe system is carried out for demonstration of the proposed integrated modeling approach. The functional deterioration of sewer pipes and the effectiveness of flushing operations that target to bring flow capacity to intact state are modeled. Influences of pipe length, diameter, slope, and sewershed area are examined. The present work is a valuable step toward development of evidence‐based risk‐informed asset management framework.

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Field assessment of a concrete bridge

Lantsoght

2018

Eco-Efficient Repair and Rehabilitation of Concrete Infrastructures

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Development of Stop Criteria for Proof Loading

Cited by 5 publications

References 14 publications

Identification of Stop Criteria for Large-Scale Laboratory Slab Tests Using Digital Image Correlation and Acoustic Emission

Identification of Stop Criteria for Large-Scale Laboratory Slab Tests Using Digital Image Correlation and Acoustic Emission

Integrative modeling of performance deterioration and maintenance effectiveness for infrastructure assets with missing condition data

Field assessment of a concrete bridge

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