Optimization of Dosage for Asphalt Volatile Harmful Gas Inhibitor Using Multi-Response Satisfaction Function and Nonlinear Regression.
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| Title: | Optimization of Dosage for Asphalt Volatile Harmful Gas Inhibitor Using Multi-Response Satisfaction Function and Nonlinear Regression. |
|---|---|
| Authors: | Liu, Zhiye1 (AUTHOR), Ren, Xiaoyu2 (AUTHOR), Du, Wenyao3 (AUTHOR) 24107017@stu.sdjtu.edu.cn, Li, Qinghang4 (AUTHOR), Guo, Dedong1,5 (AUTHOR), Xu, Meng1,6 (AUTHOR), Lu, Wei1,5 (AUTHOR), Riccardi, Chiara2,6 (AUTHOR), Li, Mengchen1,3 (AUTHOR), Zhong, Zouwei1,4 (AUTHOR) |
| Source: | Materials (1996-1944). May2026, Vol. 19 Issue 9, p1871. 15p. |
| Subjects: | Nonlinear regression, Multi-objective optimization, Asphalt, Poisonous gases |
| Abstract: | To achieve synergistic, efficient degradation of volatile, harmful gases in asphalt and to scientifically quantify inhibitor dosage, this study proposes a dosage optimization method that integrates nonlinear regression with a multi-response satisfaction function. Focusing on a proprietary composite volatile gas suppressant, we systematically measured the concentration trends of ammonia, nitrogen oxides, sulfur dioxide, and hydrogen sulfide emitted from three asphalt systems: base asphalt, SBS modified asphalt (Styrene-Butadiene-Styrene modified asphalt), and rubber modified asphalt under different suppressant dosages (0%, 0.02%, 0.04%, 0.06%, 0.08%, and 0.10%). First, high-precision prediction models (R2 > 0.95) were established using nonlinear regression to relate different inhibitor dosages to corresponding gas concentrations. Based on a satisfaction function, the multi-objective degradation effects were normalized into a comprehensive satisfaction index, and the optimal dosage was then determined. The results indicate: (1) the constructed models can accurately predict the concentrations of volatile harmful gases at various dosages; (2) the predicted optimal blending ratios vary by asphalt type, specifically 0.082% for base asphalt, 0.079% for SBS modified asphalt, and 0.080% for rubber modified asphalt; and (3) at the optimal blending ratios, all four gases achieve high and balanced degradation levels, resulting in the best overall degradation performance. At the same time, road performance tests confirmed that this blending ratio has no significant negative impact on the high-temperature and low-temperature stability or water stability of the asphalt mixture. Compared with traditional single-factor empirical methods, this approach represents a methodological upgrade from qualitative description to quantitative prediction, and from single-objective comparison to multi-objective synergistic optimization, providing data and theoretical support for the precise, efficient, and engineering-applicable use of asphalt volatile gas inhibitors. [ABSTRACT FROM AUTHOR] |
| Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 193715677 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimization of Dosage for Asphalt Volatile Harmful Gas Inhibitor Using Multi-Response Satisfaction Function and Nonlinear Regression. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Zhiye%22">Liu, Zhiye</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ren%2C+Xiaoyu%22">Ren, Xiaoyu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Du%2C+Wenyao%22">Du, Wenyao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> 24107017@stu.sdjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Qinghang%22">Li, Qinghang</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Dedong%22">Guo, Dedong</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Meng%22">Xu, Meng</searchLink><relatesTo>1,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Wei%22">Lu, Wei</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Riccardi%2C+Chiara%22">Riccardi, Chiara</searchLink><relatesTo>2,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Mengchen%22">Li, Mengchen</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhong%2C+Zouwei%22">Zhong, Zouwei</searchLink><relatesTo>1,4</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Materials+%281996-1944%29%22">Materials (1996-1944)</searchLink>. May2026, Vol. 19 Issue 9, p1871. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Nonlinear+regression%22">Nonlinear regression</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Asphalt%22">Asphalt</searchLink><br /><searchLink fieldCode="DE" term="%22Poisonous+gases%22">Poisonous gases</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: To achieve synergistic, efficient degradation of volatile, harmful gases in asphalt and to scientifically quantify inhibitor dosage, this study proposes a dosage optimization method that integrates nonlinear regression with a multi-response satisfaction function. Focusing on a proprietary composite volatile gas suppressant, we systematically measured the concentration trends of ammonia, nitrogen oxides, sulfur dioxide, and hydrogen sulfide emitted from three asphalt systems: base asphalt, SBS modified asphalt (Styrene-Butadiene-Styrene modified asphalt), and rubber modified asphalt under different suppressant dosages (0%, 0.02%, 0.04%, 0.06%, 0.08%, and 0.10%). First, high-precision prediction models (R2 > 0.95) were established using nonlinear regression to relate different inhibitor dosages to corresponding gas concentrations. Based on a satisfaction function, the multi-objective degradation effects were normalized into a comprehensive satisfaction index, and the optimal dosage was then determined. The results indicate: (1) the constructed models can accurately predict the concentrations of volatile harmful gases at various dosages; (2) the predicted optimal blending ratios vary by asphalt type, specifically 0.082% for base asphalt, 0.079% for SBS modified asphalt, and 0.080% for rubber modified asphalt; and (3) at the optimal blending ratios, all four gases achieve high and balanced degradation levels, resulting in the best overall degradation performance. At the same time, road performance tests confirmed that this blending ratio has no significant negative impact on the high-temperature and low-temperature stability or water stability of the asphalt mixture. Compared with traditional single-factor empirical methods, this approach represents a methodological upgrade from qualitative description to quantitative prediction, and from single-objective comparison to multi-objective synergistic optimization, providing data and theoretical support for the precise, efficient, and engineering-applicable use of asphalt volatile gas inhibitors. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193715677 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/ma19091871 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1871 Subjects: – SubjectFull: Nonlinear regression Type: general – SubjectFull: Multi-objective optimization Type: general – SubjectFull: Asphalt Type: general – SubjectFull: Poisonous gases Type: general Titles: – TitleFull: Optimization of Dosage for Asphalt Volatile Harmful Gas Inhibitor Using Multi-Response Satisfaction Function and Nonlinear Regression. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Zhiye – PersonEntity: Name: NameFull: Ren, Xiaoyu – PersonEntity: Name: NameFull: Du, Wenyao – PersonEntity: Name: NameFull: Li, Qinghang – PersonEntity: Name: NameFull: Guo, Dedong – PersonEntity: Name: NameFull: Xu, Meng – PersonEntity: Name: NameFull: Lu, Wei – PersonEntity: Name: NameFull: Riccardi, Chiara – PersonEntity: Name: NameFull: Li, Mengchen – PersonEntity: Name: NameFull: Zhong, Zouwei IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961944 Numbering: – Type: volume Value: 19 – Type: issue Value: 9 Titles: – TitleFull: Materials (1996-1944) Type: main |
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