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Arngbunta, Anukun
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Civil Engineering, Building, Construction & Architecture

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Strength Characteristics and Material Design of Recycled Flexible Pavement Materials Bubpi, Attaphol; Arngbunta, Anukun; Amornpinyo, Prach; Sirisriphet, Yongyuth; Tho-In, Tawatchai; Srichandum, Sakchai; Srirueng, Preechawut; Kampala, Apichit; Posi, Patcharapol; Chindaprasirt, Prinya
Civil Engineering Journal Vol. 11 No. 12 (2025): December
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-12-021

Abstract

This study develops a strength-based mix-design framework for rehabilitating flexible pavements using reclaimed asphalt pavement (RAP) blended with crushed rock (CR) and cement. Objectives were to quantify 7-day unconfined compressive strength (UCS) as a function of mixture variables and to provide field-ready proportioning equations. Methods comprised laboratory testing of RAP–CR blends (RAP = 0–100%) with 2–5% cement, Modified Proctor compaction, and 7-day UCS; regression related UCS to a modified parameter (w/c)(1−k·AS), where asphalt content (AS) is obtained from AS = 0.04·RAP. Findings show that increasing RAP lowers dry density (2.31→2.11 g/cm³) and raises optimum moisture (5.03→7.17%). The 7-day prediction is qᵤ,7 = 23.44/[(w/c)(1−0.22·AS)]0.677 (R² = 0.863). A worked example (4-cm asphalt over a 20-cm base; 20-cm milling) gives RAP = 20%, AS = 0.80, recommended w/c = 1.31, and cement = 4.03% at OMC = 5.28% and dry density = 2.276 g/cm³, satisfying 1.72 MPa (17.5 kg/cm²) at 7 days. Novelty/Improvement: the framework consolidates RAP content and binder effects into a single modified w/c parameter, enabling rapid, transparent proportioning for construction control. Broader impacts include reduced demand for virgin aggregate and haul-off of demolition debris, fewer truck movements and landfill burdens, and potential life-cycle cost savings in network-level rehabilitation.
Development and Calibration of Empirical and Statistical Models for SPT-N Prediction in Fine Grained Soils Kampala , Apichit; Thirakultomorn , Tinn; Arngbunta, Anukun; Kaewhanam , Nopanom; Amornpinyo, Prach; Sirisriphet , Yongyuth; Bubpi, Attaphol
Civil Engineering Journal Vol. 12 No. 3 (2026): March
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2026-012-03-020

Abstract

This study aims to develop and calibrate predictive models for the Standard Penetration Test number (N-SPT) in cohesive soils with a Liquid Limit between 20% and 60%. The objectives were to evaluate and compare empirical estimations based on the Consistency Index (CI) against statistical models derived from Multiple Linear Regression (MLR). Methods involved the analysis of a comprehensive dataset containing 469 samples obtained from the Thailand-China High-Speed Railway project and established literature, utilizing soil index properties (Liquid Limit (LL), Plastic Limit (PL), and water content (wn)) alongside unit weight (γ) as independent variables. Findings demonstrate that the MLR model provides significantly higher predictive reliability with a coefficient of determination (R2) of 0.982, compared to the empirical method (R2 = 0.667). To enhance practical application, both models were calibrated using a 90% confidence level modification factor. Novelty/Improvement: This research identifies unit weight as a critical parameter that, when integrated with index properties, substantially improves the accuracy of N-SPT estimations. The resulting framework provides geotechnical engineers with a validated, high-precision tool for soil strength estimation, effectively accelerating soil investigation processes while maintaining high reliability in design parameters.
Co-Authors Amornpinyo, Prach Bubpi, Attaphol Chindaprasirt, Prinya Kaewhanam , Nopanom Kampala , Apichit Kampala, Apichit Posi, Patcharapol Sirisriphet , Yongyuth Sirisriphet, Yongyuth Srichandum, Sakchai Srirueng, Preechawut Thirakultomorn , Tinn Tho-In, Tawatchai