Fuzzy based state assessment for reinforced concrete building structures

Kim, Yeong Min; Kim, Chee Kyeong; Hong, Sung Gul

doi:10.1016/j.engstruct.2005.12.011

Cited by 34 publications

(8 citation statements)

References 14 publications

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“…32,33 (1) ,34 (1) ,35 (2) (30 (1) ,31 (2) ) examples and the corresponding diagnosis results were extracted from the technical manuals published by Japanese Concrete Institute [12]. Five types of cracks, that is, four wall cracks and one slab crack, generated in four structures were chosen as application examples.…”

Section: Decision Attributes (Q)mentioning

confidence: 99%

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Rough set algorithm for crack category determination of reinforced concrete structures

Kim¹,

Kim

Lee

2009

Advances in Engineering Software

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Section: Decision Attributes (Q)mentioning

confidence: 99%

“…The maintenance activities for concrete structures are required to maintain and enhance the usability and durability of structures throughout their life cycle [1]. Concrete structures are damaged and deteriorated by various causes; among them cracks act as a primary cause of decreased structural capacity, durability, waterproofing, etc.…”

Section: Introductionmentioning

confidence: 99%

Rough set algorithm for crack category determination of reinforced concrete structures

Kim¹,

Kim

Lee

2009

Advances in Engineering Software

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“…Various research works have been carried out for uncertainty analysis in structural design (Biondini et al 2004; Moller & Beer 2004;Moller et al 2003;Kim et al 2006;Noor et al 2001;Ben-Haim & Elishakoff 1990;Elishakoff 1999;Pantelides & Booth 1999;Akkurt et al 2003). For reasonable computer expenses, only the most important variables should be treated statistically.…”

Section: Introductionmentioning

confidence: 98%

Uncertainty modelling of critical column buckling for reinforced concrete buildings

Korkmaz

Demir

Tekeli

2011

Sadhana

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Buckling is a critical issue for structural stability in structural design. In most of the buckling analyses, applied loads, structural and material properties are considered certain. However, in reality, these parameters are uncertain. Therefore, a prognostic solution is necessary and uncertainties have to be considered. Fuzzy logic algorithms can be a solution to generate more dependable results. This study investigates the material uncertainties on column design and proposes an uncertainty model for critical column buckling reinforced concrete buildings. Fuzzy logic algorithm was employed in the study. Lower and upper bounds of elastic modulus representing material properties were defined to take uncertainties into account. The results show that uncertainties play an important role in stability analyses and should be considered in the design. The proposed approach is applicable to both future numerical and experimental researches. According to the study results, it is seen that, calculated buckling load values are stayed in lower and upper bounds while the load values are different for same concrete strength values by using different code formula.

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“…Sci. 2017, 7, 518 2 of 16 has been also utilized for many decision-making procedures in the civil engineering fields [8][9][10][11][12][13]. For instance, Rao et al [8] and Mo et al [9] applied fuzzy theory for the optimization of their structural or engineering design.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Rao et al [8] and Mo et al [9] applied fuzzy theory for the optimization of their structural or engineering design. Kim et al [10,11] introduced a fuzzy-based assessment method to estimate the durability and serviceability performances of reinforced concrete buildings and also developed the crack diagnosis system that can identify the primary causes of cracks. Cho et al [12] developed the remaining service life evaluation method of concrete buildings by utilizing fuzzy theory, which can consider the effects of multiple influencing factors on the deterioration of durability.…”

Section: Introductionmentioning

confidence: 99%

Fire Damage Assessment of Reinforced Concrete Structures Using Fuzzy Theory

Cho

Lee

et al. 2017

Applied Sciences

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Abstract:Once a reinforced concrete (RC) structure is damaged by fire, the fire damage assessment should proceed to take appropriate post-fire actions, including the decision-making of whether it can be repaired for reuse or not. Since the assessment results of current fire damage diagnosis methods, however, highly depend on the subjective judgment of inspectors, it is hard to ensure their objectiveness and reliability. This study, therefore, aims to develop a new fire damage diagnosis system (FDDS) based on fuzzy theory that can provide objective and comprehensive evaluation results by considering all of the damage conditions observed from the inspection on RC structural members exposed to fire. In addition, the FDDS was applied to an actual fire-damaged case reported by the Architectural Institute of Japan (AIJ, 2009), and it appears that the proposed method provides a reasonable estimation on the fire damage grade of the fire-damaged RC members.

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Fuzzy based state assessment for reinforced concrete building structures

Cited by 34 publications

References 14 publications

Rough set algorithm for crack category determination of reinforced concrete structures

Rough set algorithm for crack category determination of reinforced concrete structures

Uncertainty modelling of critical column buckling for reinforced concrete buildings

Fire Damage Assessment of Reinforced Concrete Structures Using Fuzzy Theory

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