Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm
Here, we develop a model predicting the dynamic moduli of hot-mix asphalt/concrete using the extended Kalman filter (EKF) algorithm and draw frequency-domain master curves. Discrete dynamic moduli were obtained via impact resonance tests (IRTs) on linear viscoelastic (LVE) asphalt at 20, 30, 35, 40,...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/3089085 |
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| author | Yu-Seok Gong Dowan Kim Sungho Mun |
| author_facet | Yu-Seok Gong Dowan Kim Sungho Mun |
| author_sort | Yu-Seok Gong |
| collection | DOAJ |
| description | Here, we develop a model predicting the dynamic moduli of hot-mix asphalt/concrete using the extended Kalman filter (EKF) algorithm and draw frequency-domain master curves. Discrete dynamic moduli were obtained via impact resonance tests (IRTs) on linear viscoelastic (LVE) asphalt at 20, 30, 35, 40, and 50°C. Typically, viscoelastic characteristics have been used to derive asphalt dynamic moduli; compressive frequency sweep tests at different frequencies (Hz) and temperatures are employed to this end. We compared IRT-derived viscoelastic master curves obtained via compressive frequency sweep testing to those derived using the EKF algorithm, which employs a nonlinear sigmoidal curve and a Taylor series to explore the viscoelastic function. The model reduced errors at both low and high frequencies by correcting the coefficients of the master curve. Furthermore, the predictive model effectively estimated dynamic moduli at various frequencies, and also root-mean-square errors (RMSEs) which, together with the mean percentage errors (MPEs), were used to compare predictions. |
| format | Article |
| id | doaj-art-f7a87fdbef1f4956ae967301d83082ef |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-f7a87fdbef1f4956ae967301d83082ef2025-02-03T06:13:11ZengWileyAdvances in Civil Engineering1687-80861687-80942018-01-01201810.1155/2018/30890853089085Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter AlgorithmYu-Seok Gong0Dowan Kim1Sungho Mun2Highway and Transportation Technology Institute, Korea Expressway Corporation, 208-96, Dongbu-daero 922 Beon-Gil, Dongtan-Myeon, Hwaseong-Si 18489, Gyeonggi-Do, Republic of KoreaDepartment of Road & Airport, Kunhwa Engineering & Consulting Co., Ltd., 321 Teheran-Ro, Gangnam-Gu, Seoul, Republic of KoreaDepartment of Civil Engineering, Seoul National University of Science & Technology, 232 Gongneung-Ro, Nowon-Gu, Seoul 01811, Republic of KoreaHere, we develop a model predicting the dynamic moduli of hot-mix asphalt/concrete using the extended Kalman filter (EKF) algorithm and draw frequency-domain master curves. Discrete dynamic moduli were obtained via impact resonance tests (IRTs) on linear viscoelastic (LVE) asphalt at 20, 30, 35, 40, and 50°C. Typically, viscoelastic characteristics have been used to derive asphalt dynamic moduli; compressive frequency sweep tests at different frequencies (Hz) and temperatures are employed to this end. We compared IRT-derived viscoelastic master curves obtained via compressive frequency sweep testing to those derived using the EKF algorithm, which employs a nonlinear sigmoidal curve and a Taylor series to explore the viscoelastic function. The model reduced errors at both low and high frequencies by correcting the coefficients of the master curve. Furthermore, the predictive model effectively estimated dynamic moduli at various frequencies, and also root-mean-square errors (RMSEs) which, together with the mean percentage errors (MPEs), were used to compare predictions.http://dx.doi.org/10.1155/2018/3089085 |
| spellingShingle | Yu-Seok Gong Dowan Kim Sungho Mun Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm Advances in Civil Engineering |
| title | Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm |
| title_full | Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm |
| title_fullStr | Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm |
| title_full_unstemmed | Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm |
| title_short | Estimation of the Dynamic Moduli of Viscoelastic Asphalt Mixtures Using the Extended Kalman Filter Algorithm |
| title_sort | estimation of the dynamic moduli of viscoelastic asphalt mixtures using the extended kalman filter algorithm |
| url | http://dx.doi.org/10.1155/2018/3089085 |
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