Benchmark Problems for AAR FEA Code Validation

Saouma, Victor E.; Sellier, Alain; Multon, Stéphane; Pape, Yann Le

doi:10.1007/978-3-030-44014-5_21

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…ASR-related damage is distinguished by its map cracking pattern [4] that frequently appears on concrete surfaces and can be readily visible, serving as an early indicator of potential damage in concrete structures. Monitoring cracks over time provides critical insights into the progression of damage, as the presence of the ASR can result in harmful distress to concrete mechanical properties, stiffness, serviceability, and durability [5]. However, assessing the presence and severity of cracks remains an initial step in evaluating the overall condition of the concrete structure [3].…”

Section: Introductionmentioning

confidence: 99%

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An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces

Zhang,

Trottier,

Sanchez

et al. 2024

Materials

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Concrete surface cracks serve as early indicators of potential structural threats. Visual inspection, a commonly used and versatile concrete condition assessment technique, is employed to assess concrete degradation by observing signs of damage on the surface level. However, the method tends to be qualitative and needs to be more comprehensive in providing accurate information regarding the extent of damage and its evolution, notwithstanding its time-consuming and environment-sensitive nature. As such, the integration of image analysis techniques with artificial intelligence (AI) has been increasingly proven efficient as a tool to capture damage signs on concrete surfaces. However, to improve the performance of automated crack detection, it is imperative to intensively train a machine learning model, and questions remain regarding the required image quality and image collection methodology needed to ensure the model’s accuracy and reliability in damage quantitative analysis. This study aims to establish a procedure for image acquisition and processing through the application of an image-based measurement approach to explore the capabilities of concrete surface damage diagnosis. Digitizing crack intensity measurements were found to be feasible; however, larger datasets are required. Due to the anisotropic behavior of the damage, the model’s ability to capture crack directionality was developed, presenting no statistically significant differences between the observed and predicted values used in this study with correlation coefficients of 0.79 and 0.82.

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Section: Introductionmentioning

confidence: 99%

“…Materials 2024, 17, x FOR PEER REVIEW 2 of 26 crete mechanical properties, stiffness, serviceability, and durability [5]. However, assessing the presence and severity of cracks remains an initial step in evaluating the overall condition of the concrete structure [3].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces

Zhang,

Trottier,

Sanchez

et al. 2024

Materials

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“…However, generally, SPs contain sodium and/or potassium, which can increase the alkalinity of the pore solution within the concrete, resulting in alkali-silica reaction (ASR) deterioration. The latter is among the principal sources of early deterioration in concrete, impacting the durability, serviceability, and performance of concrete [4,5]. Very few works have evaluated the effects of various SPs on ASR-induced development, and consequently, the effects of distinct types of SPs on ASR-induced development (i.e., kinetics and induced expansion, damage generation, and propagation, as well as mechanical degradation) remain unknown.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Distinct Superplasticizers on the Degradation of Concrete Affected by Alkali-Silica Reaction (ASR)

et al. 2023

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The effect of two superplasticizers (SPs) with various equivalent (eq.) alkali contents (i.e., with 0.00009% and 4.1% of Na2Oeq, respectively) on the development of an alkali-silica reaction (ASR) was investigated through the use of multilevel assessment. This testing protocol showed promising results for evaluating concrete damage due to ASRs based on mechanical and microscopical testing protocols, specifically the stiffness damage test (SDT) and the damage rating index (DRI). Concrete specimens that incorporated the aforementioned SPs and distinct reactive aggregates (coarse and fine) were manufactured and then stored in conditions that enabled ASR development and were monitored over time. Upon reaching the desired expansion levels of this study, the concrete specimens were prepared for the multilevel assessment. The results show that the SP-incorporated concrete specimens with lower and higher alkali content yielded lower and higher deterioration results, respectively. This clearly confirms that while SP-incorporated concrete that contains SPs with a higher alkali content could increase the risk of ASR deterioration, those SPs with a very low amount of alkali content could act as a mitigation strategy against ASRs. Finally, an investigation into the influence of distinct SPs on the chemical composition of an ASR gel was conducted, which confirmed that the SP with a higher alkali content had the highest potential for further deterioration.

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Verification, validation, and uncertainty quantification (VVUQ) in structural analysis of concrete dams

Salamon,

Hariri-Ardebili

2024

Front. Built Environ.

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Over the past three decades, advancements in computational power and numerical methods have significantly enhanced the role of structural analyses in the design and safety assessment of dams. Simulating concrete dam behavior, particularly in interactions with reservoir water and rock foundations, poses formidable computational challenges. Additionally, the need to define uncertainties related to material parameters, loading conditions, and modeling strategy adds complexity to the modeling process, therefore, quantifying sources of uncertainty is crucial for maintaining credibility and confidence in analysis results. This paper provides a synthesis and an overview of existing research and presents a generic framework for evaluating the credibility of advanced structural analysis methods for concrete dams, with a focus on their limitations and associated uncertainties. The methodology includes a comprehensive process for structural analysis, verification, validation, and uncertainty quantification, aiming to facilitate condition assessments of concrete dams.

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Benchmark Problems for AAR FEA Code Validation

Cited by 3 publications

References 7 publications

An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces

An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces

The Impact of Distinct Superplasticizers on the Degradation of Concrete Affected by Alkali-Silica Reaction (ASR)

Verification, validation, and uncertainty quantification (VVUQ) in structural analysis of concrete dams

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