Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica
The present research aims to conduct laboratory assessment on fatigue phenomenon in warm mix asphalt modified with nano-silica and including reclaimed asphalt pavement materials by the aid of review on self-healing behavior and measurement of validity of laboratory results by modeling via neural art...
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| Format: | Article |
| Language: | English |
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Semnan University
2020-05-01
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| Series: | Journal of Rehabilitation in Civil Engineering |
| Subjects: | |
| Online Access: | https://civiljournal.semnan.ac.ir/article_4072_5c5bc4d75b3996d4f34052694d07928b.pdf |
| _version_ | 1818157131905368064 |
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| author | Saber Kie Badroodi Mahmood Reza Keymanesh Gholamali Shafabakhsh |
| author_facet | Saber Kie Badroodi Mahmood Reza Keymanesh Gholamali Shafabakhsh |
| author_sort | Saber Kie Badroodi |
| collection | DOAJ |
| description | The present research aims to conduct laboratory assessment on fatigue phenomenon in warm mix asphalt modified with nano-silica and including reclaimed asphalt pavement materials by the aid of review on self-healing behavior and measurement of validity of laboratory results by modeling via neural artificial network in neutral network of SPSS software. For this purpose, 2% weight of sasobit and 3, 5 and 7 % weights of base bitumen-to-bitumen (85-100) were added and they were stirred up by high-cut mixer. Then, the specimens of four-point flexural test were made by the reclaimed bitumen samples. The quantities of 0, 70 and 100% of reclaimed asphalt materials were utilized for aging simulation process in warm mix asphalt to build four-point flexural tested slabs. The findings indicate that adding nano-silica may essentially affect rising self-healing level in warm mix asphalts. The current study intends to present a model based on neural artificial network technique to predict behavior of warm asphalt specimens including different nano-material contents and to compare them with the laboratory results for measurement of validity of the given model. The given results show high precision of the model at level of 0.951. |
| first_indexed | 2024-12-11T15:09:19Z |
| format | Article |
| id | doaj.art-a730a09a93b5487d892bb60410da716c |
| institution | Directory Open Access Journal |
| issn | 2345-4415 2345-4423 |
| language | English |
| last_indexed | 2024-12-11T15:09:19Z |
| publishDate | 2020-05-01 |
| publisher | Semnan University |
| record_format | Article |
| series | Journal of Rehabilitation in Civil Engineering |
| spelling | doaj.art-a730a09a93b5487d892bb60410da716c2022-12-22T01:00:48ZengSemnan UniversityJournal of Rehabilitation in Civil Engineering2345-44152345-44232020-05-01829211310.22075/jrce.2019.17478.13314072Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-SilicaSaber Kie Badroodi0Mahmood Reza Keymanesh1Gholamali Shafabakhsh2Ph.D. candidate of Tehran PNU University, Tehran, IranAssociate Professor, North Tehran Branch, Payam Noor UniversityFaculty of Civil Engineering, Semnan UniversityThe present research aims to conduct laboratory assessment on fatigue phenomenon in warm mix asphalt modified with nano-silica and including reclaimed asphalt pavement materials by the aid of review on self-healing behavior and measurement of validity of laboratory results by modeling via neural artificial network in neutral network of SPSS software. For this purpose, 2% weight of sasobit and 3, 5 and 7 % weights of base bitumen-to-bitumen (85-100) were added and they were stirred up by high-cut mixer. Then, the specimens of four-point flexural test were made by the reclaimed bitumen samples. The quantities of 0, 70 and 100% of reclaimed asphalt materials were utilized for aging simulation process in warm mix asphalt to build four-point flexural tested slabs. The findings indicate that adding nano-silica may essentially affect rising self-healing level in warm mix asphalts. The current study intends to present a model based on neural artificial network technique to predict behavior of warm asphalt specimens including different nano-material contents and to compare them with the laboratory results for measurement of validity of the given model. The given results show high precision of the model at level of 0.951.https://civiljournal.semnan.ac.ir/article_4072_5c5bc4d75b3996d4f34052694d07928b.pdfwarm mix asphaltfatigueself-healingreclaimed asphalt materialsnano-silicaneural network |
| spellingShingle | Saber Kie Badroodi Mahmood Reza Keymanesh Gholamali Shafabakhsh Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica Journal of Rehabilitation in Civil Engineering warm mix asphalt fatigue self-healing reclaimed asphalt materials nano-silica neural network |
| title | Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica |
| title_full | Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica |
| title_fullStr | Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica |
| title_full_unstemmed | Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica |
| title_short | Laboratory Study and Investigation on Significance Level of Fatigue Phenomenon in Warm Mix Asphalt Modified with Nano-Silica |
| title_sort | laboratory study and investigation on significance level of fatigue phenomenon in warm mix asphalt modified with nano silica |
| topic | warm mix asphalt fatigue self-healing reclaimed asphalt materials nano-silica neural network |
| url | https://civiljournal.semnan.ac.ir/article_4072_5c5bc4d75b3996d4f34052694d07928b.pdf |
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