Integration of a Hybrid Method into an Efficient Reliability-Based Design Optimization Technique for Large Structures Article Swipe
Nader M. Okasha
,
Osama Ahmed Mohamed
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/603/4/042039
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/603/4/042039
The computational burden imposed by the repetitive and lengthy nature of the structural analyses of large structures has lead researches to continuously devise efficient methods for conducting their reliability analysis in addition to powerful methods for solving the design optimization problem. The presence of a considerably large number of random variables in the reliability analyses of large structure is another issue that tends to slow down the design optimization problem. In this paper, a hybrid method that was recently presented by the first author will be integrated into a structural reliability-based design optimization technique for large structures. In this technique, modified concepts of the weighted average simulation method are used to determine the most probable point of failure in a computationally efficient manner. The most probable point of failure is then transferred into the standard normal space, where the reliability index is calculated in closed-form. The firefly algorithm will be used for solving the optimization problem. It will be shown that the integrated approach significantly reduces the computational resources required for solving the design problem. The technique will be tested on a truss bridge. The results will shed light on the efficiency of the proposed technique in solving reliability-based design optimization problems.
Related Topics
Concepts
Reliability (semiconductor)
Truss
Computer science
Mathematical optimization
Firefly algorithm
Point (geometry)
Bridge (graph theory)
Optimization problem
Reliability engineering
Algorithm
Mathematics
Engineering
Particle swarm optimization
Structural engineering
Power (physics)
Internal medicine
Geometry
Physics
Quantum mechanics
Medicine
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1757-899x/603/4/042039
- https://iopscience.iop.org/article/10.1088/1757-899X/603/4/042039/pdf
- OA Status
- diamond
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2973632107
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2973632107Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1757-899x/603/4/042039Digital Object Identifier
- Title
-
Integration of a Hybrid Method into an Efficient Reliability-Based Design Optimization Technique for Large StructuresWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-09-01Full publication date if available
- Authors
-
Nader M. Okasha, Osama Ahmed MohamedList of authors in order
- Landing page
-
https://doi.org/10.1088/1757-899x/603/4/042039Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1757-899X/603/4/042039/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1757-899X/603/4/042039/pdfDirect OA link when available
- Concepts
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Reliability (semiconductor), Truss, Computer science, Mathematical optimization, Firefly algorithm, Point (geometry), Bridge (graph theory), Optimization problem, Reliability engineering, Algorithm, Mathematics, Engineering, Particle swarm optimization, Structural engineering, Power (physics), Internal medicine, Geometry, Physics, Quantum mechanics, MedicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.was | 78 |
| abstract_inverted_index.down | 66 |
| abstract_inverted_index.into | 88, 133 |
| abstract_inverted_index.lead | 19 |
| abstract_inverted_index.most | 114, 125 |
| abstract_inverted_index.shed | 188 |
| abstract_inverted_index.slow | 65 |
| abstract_inverted_index.that | 62, 77, 161 |
| abstract_inverted_index.then | 131 |
| abstract_inverted_index.this | 72, 99 |
| abstract_inverted_index.used | 110, 151 |
| abstract_inverted_index.will | 85, 149, 158, 178, 187 |
| abstract_inverted_index.first | 83 |
| abstract_inverted_index.index | 141 |
| abstract_inverted_index.issue | 61 |
| abstract_inverted_index.large | 16, 47, 57, 96 |
| abstract_inverted_index.light | 189 |
| abstract_inverted_index.point | 116, 127 |
| abstract_inverted_index.shown | 160 |
| abstract_inverted_index.tends | 63 |
| abstract_inverted_index.their | 28 |
| abstract_inverted_index.truss | 183 |
| abstract_inverted_index.where | 138 |
| abstract_inverted_index.author | 84 |
| abstract_inverted_index.burden | 3 |
| abstract_inverted_index.design | 39, 68, 92, 174, 200 |
| abstract_inverted_index.devise | 23 |
| abstract_inverted_index.hybrid | 75 |
| abstract_inverted_index.method | 76, 108 |
| abstract_inverted_index.nature | 10 |
| abstract_inverted_index.normal | 136 |
| abstract_inverted_index.number | 48 |
| abstract_inverted_index.paper, | 73 |
| abstract_inverted_index.random | 50 |
| abstract_inverted_index.space, | 137 |
| abstract_inverted_index.tested | 180 |
| abstract_inverted_index.another | 60 |
| abstract_inverted_index.average | 106 |
| abstract_inverted_index.bridge. | 184 |
| abstract_inverted_index.failure | 118, 129 |
| abstract_inverted_index.firefly | 147 |
| abstract_inverted_index.imposed | 4 |
| abstract_inverted_index.lengthy | 9 |
| abstract_inverted_index.manner. | 123 |
| abstract_inverted_index.methods | 25, 35 |
| abstract_inverted_index.reduces | 166 |
| abstract_inverted_index.results | 186 |
| abstract_inverted_index.solving | 37, 153, 172, 198 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.addition | 32 |
| abstract_inverted_index.analyses | 14, 55 |
| abstract_inverted_index.analysis | 30 |
| abstract_inverted_index.approach | 164 |
| abstract_inverted_index.concepts | 102 |
| abstract_inverted_index.modified | 101 |
| abstract_inverted_index.powerful | 34 |
| abstract_inverted_index.presence | 43 |
| abstract_inverted_index.probable | 115, 126 |
| abstract_inverted_index.problem. | 41, 70, 156, 175 |
| abstract_inverted_index.proposed | 195 |
| abstract_inverted_index.recently | 79 |
| abstract_inverted_index.required | 170 |
| abstract_inverted_index.standard | 135 |
| abstract_inverted_index.weighted | 105 |
| abstract_inverted_index.algorithm | 148 |
| abstract_inverted_index.determine | 112 |
| abstract_inverted_index.efficient | 24, 122 |
| abstract_inverted_index.presented | 80 |
| abstract_inverted_index.problems. | 202 |
| abstract_inverted_index.resources | 169 |
| abstract_inverted_index.structure | 58 |
| abstract_inverted_index.technique | 94, 177, 196 |
| abstract_inverted_index.variables | 51 |
| abstract_inverted_index.calculated | 143 |
| abstract_inverted_index.conducting | 27 |
| abstract_inverted_index.efficiency | 192 |
| abstract_inverted_index.integrated | 87, 163 |
| abstract_inverted_index.repetitive | 7 |
| abstract_inverted_index.researches | 20 |
| abstract_inverted_index.simulation | 107 |
| abstract_inverted_index.structural | 13, 90 |
| abstract_inverted_index.structures | 17 |
| abstract_inverted_index.technique, | 100 |
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| abstract_inverted_index.computational | 2, 168 |
| abstract_inverted_index.significantly | 165 |
| abstract_inverted_index.computationally | 121 |
| abstract_inverted_index.reliability-based | 91, 199 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5000360753 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I117222138 |
| citation_normalized_percentile.value | 0.14914425 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |