journal article·2025-07Open access

ECC-enhanced aluminum dowels: A solution for better load transfer in rigid concrete pavements

Mohamed Emara, Taher A. Tawfik, Mohamed Ghalla, Galal Elsamak, Ali Basha, Ahmed Badr el-din

Abstract

This study evaluates aluminum boxes as dowels to improve the performance of joined plain concrete pavement (JPCP). Nine specimens, divided into three groups, examined the effects of dowel embedment length (three, four, and five times the box width), end anchors, and engineered cementitious composites (ECC) on joint behavior. Increasing dowel length enhanced load transfer efficiency and crack patterns, while end anchors improved crack distribution by preventing dowel-concrete debonding. Embedment length significantly influenced ultimate load capacity, with the first and third groups showing a 28 % average increase and the second group a 21 % gain. End anchors boosted yielding load by 12 % and ultimate load by 60 %. ECC further improved performance, increasing ultimate load by 62 % and yielding load by 27 %. Extended embedment length enhanced energy absorption, with normal concrete (NC) specimens achieving 25 %-54 % increases, ECC specimens showing 16 %-41 % gains, and NC specimens with anchored dowels exhibiting 20 %-43 % improvements. Finally, a finite element model developed to simulate the behavior of the tested specimens showed good agreement with the experimental data. • Optimized dowel lengths and anchors improved load transfer and crack control in JPCPs. • ECC boosted ultimate load capacity by 62 % and yielding load by 27 %, outperforming other enhancements. • Energy absorption increased by up to 54 %, showing improved durability and resilience. • Finite element modeling matched experimental results, validating findings and offering predictions.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Innovative concrete reinforcement materials · Structural Behavior of Reinforced Concrete · Concrete and Cement Materials Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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