2D Random Shape of Aggregate Model Using Image Processing and Convex Combination Theory Article Swipe
Ultrasonic non-destructive testing (UNDT) is used for detecting and locating damage in concrete structures such as bridge decks and pavement. There are even advanced UNDT methods such as the incoherent back-scattering approach that is one of the effective methods to characterize the distributed micro-cracks in the homogeneous concrete infrastructures sensitively. However, the shape and orientation of the aggregates play an integral role in wave reflection, refraction, and mode conversion from internal inclusions. Moreover, the micro-cracks also tend to go deeply into the inter-facial transition zone. The numerical simulation of such advanced UNDT helps to understand and predict this physical phenomenon, but requires the existence of realistic shaped coarse aggregates to understand the wave propagation phenomenon accurately. Therefore, this study presents a 2D mesoscale heterogeneous model for concrete in which the coarse aggregate shape and location are randomly generated and placed in the mortar matrix to construct a random shaped aggregate model. To achieve this goal, a morphological study was carried out on a thousand of aggregates using the image processing technique to characterize their shapes and categorize them into the three major classes: round, crushed, and needle shape aggregates. By implementing statistical analysis and the convex combination theory, the randomly generated aggregate model was developed for each class, which is derived from the real aggregate image using plain formulation. Consequently, by using the obtained parameters, a 2D convex combination theory based random shape aggregate model (CCT- RSAM) was generated which can be used in construction of the random aggregate structures.
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- Type
- article
- Language
- en
- Landing Page
- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3661104
- OA Status
- green
- Cited By
- 3
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3188553107
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3188553107Canonical identifier for this work in OpenAlex
- Title
-
2D Random Shape of Aggregate Model Using Image Processing and Convex Combination TheoryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
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2018-01-01Full publication date if available
- Authors
-
Suyun Ham, Amin Darabnoush TehraniList of authors in order
- Landing page
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https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3661104Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3661104Direct OA link when available
- Concepts
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Aggregate (composite), Reflection (computer programming), Computer science, Matrix (chemical analysis), Regular polygon, Statistical physics, Geometry, Mathematics, Materials science, Physics, Composite material, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2020: 3Per-year citation counts (last 5 years)
- Related works (count)
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20Other works algorithmically related by OpenAlex
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| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.73409765 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |