This study presents the effects of recycled concrete aggregate (RCA) on the key fresh and hardened properties of concrete. RCA was used to produce high-workability concrete substituting 0-100% natural coarse aggregate (NCA) by weight. The slump and slump flow of fresh concretes were determined to ensure high workability. In addition, the compressive, flexural and splitting tensile strengths, modulus of elasticity, and permeable voids of hardened concretes were determined. The test results revealed that RCA significantly decreased the workability of concrete. RCA also affected the compressive strength, modulus of elasticity, and permeable voids of concrete. At the age of 28 days, the concrete with 100% RCA provided 12.2% lower compressive strength and 17.7% lesser modulus of elasticity than the control concrete. Also, 100% RCA increased the permeable voids of 28-day old concrete by 8.2%. However, no significant negative impact of RCA was observed on the flexural and splitting tensile strengths of concrete.

Uncontrolled dumping of palm oil fuel ash (POFA) not only occupies valuable land but also creates environmental pollution and health hazard. These problems can be reduced to a large extent by using POFA in concrete. A number of research works have been carried out to investigate the potential of POFA for use as a supplementary cementing material in normal, high strength, high performance, and aerated concretes. This paper presents a review on the use of POFA in different types of concrete. It firstly discusses the physical and chemical properties of POFA. Then the emphasis has been given on the effects of POFA on the fresh and hardened properties, and durability of concrete. This paper shows that both ground and unground POFA increase the water demand and thus decrease the workability of concrete. However, ground POFA has shown a good potential for improving the hardened properties and durability of concrete due to its satisfactory micro-filling ability and pozzolanic activity. In addition to discussing the benefits of POFA, this study has identified certain gaps in the present state of knowledge on POFA concrete, and listed several research needs for future investigation. The findings of this study would encourage the use of POFA as a supplementary cementing material for concrete. Santrauka Nekontroliuojami palmių aliejaus kuro pelenų (POFA) sąvartynai ne tik užima vertingus žemės plotus, bet ir teršia aplinką bei kelia pavojų sveikatai. Šios problemos gali būti sumažintos POFA naudojant betone. Daug mokslinių tyrimų buvo atlikta siekiant ištirti POFA potencialą, kad juos būtų galima naudoti kaip papildomą normalių, didelio stiprio, aukštos kokybės ir poringujų betonų cementavimo medžiagą. Šiame straipsnyje apžvelgiama, kaip POFA naudojami įvairių tipų betonams. Visų pirma aptariamos fizinės ir cheminės POFA savybės. Tuomet dėmesys atkreipiamas į šviežio ir sukietėjusio betono savybes bei betono ilgaamžiškuma. Šis straipsnis parodo, kad tiek malti, tiek nemalti POFA padidina vandens poreikį ir blogina technologines charakteristikas. Tačiau malti POFA parodė potencialą gerinant betono atsparumo ir ilgaamžiškumo savybes, nes jie pasižymi geromis mikroužpildų savybėmis ir pucolaniniu aktyvumu. Be to, aptarta POFA nauda, nustatytos tam tikros šiuo metu turimų žinių apie POFA betoną spragos ir išvardyta daugelis tyrimų, kurie turėtų būti atlikti ateityje. Šio darbo išvados turėtųpaskatinti naudoti POFA kaip papildomą rišamąją betono medžiagą.

Modeling is a very useful method for the performance prediction of concrete. Most of the models available in literature are related to the compressive strength because it is a major mechanical property used in concrete design. Many attempts were taken to develop suitable mathematical models for the prediction of compressive strength of different concretes, but not for self-consolidating high-strength concrete (SCHSC) containing palm oil fuel ash (POFA). The present study has used artificial neural networks (ANN) to predict the compressive strength of SCHSC incorporating POFA. The ANN model has been developed and validated in this research using the mix proportioning and experimental strength data of 20 different SCHSC mixes. Seventy percent (70%) of the data were used to carry out the training of the ANN model. The remaining 30% of the data were used for testing the model. The training of the ANN model was stopped when the root mean square error (RMSE) and the percentage of good patterns was 0.001 and ≈100%, respectively. The predicted compressive strength values obtained from the trained ANN model were much closer to the experimental values of compressive strength. The coefficient of determination (R2) for the relationship between the predicted and experimental compressive strengths was 0.9486, which shows the higher degree of accuracy of the network pattern. Furthermore, the predicted compressive strength was found very close to the experimental compressive strength during the testing process of the ANN model. The absolute and percentage relative errors in the testing process were significantly low with a mean value of 1.74 MPa and 3.13%, respectively, which indicated that the compressive strength of SCHSC including POFA can be efficiently predicted by the ANN.

Abstract