Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char:A statistical neural network approach

The goals of this study are to assess the viability of waste tire-derived char(WTDC)as a sustainable,low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network(SCNN)model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC.The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures(WTDC-MAM).The input variables comprised waste tire char content and asphalt binder content.The output variables comprised mixture unit weight,total voids,voids filled with asphalt,Marshall stability,and flow.Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures.For predictive modeling,the SCNN model is employed,incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability.The optimal network architecture,using the collected dataset,was a 2:6:5 structure,and the neural network was trained with 60%of the data,whereas the other 20%was used for cross-validation and testing respectively.The network employed a hyperbolic tangent(tanh)activation function and a feed-forward backpropagation.According to the results,the network model could accurately predict the volumetric and Marshall properties.The predicted accuracy of SCNN was found to be as high value>98%and low prediction errors for both volumetric and Marshall properties.This study demonstrates WTDC's potential as a low-cost,sustainable aggregate replacement.The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

Application and circular economy prospects of palm oil waste for eco-friendly asphalt pavement industry:A review

During the production of palm oil,a significant amount of waste is generated.However,because of inefficient handling and utilization,these wastes are becoming a larger issue.As a result,one initiative is to use these wastes in the pavement industry as sustainable materials.However,there is still a lack of understanding about the wider incorporation of palm oil waste in asphalt pavement and its performance.This study examines existing literature on the use of various wastes in the pavement industry,including palm oil clinker(POC),palm oil fibre(POF),palm kernel shell(PKS),and palm oil fuel ash(POFA).As a result,this paper presents a systematic review and scientometric investigation of related study publications on many uses of palm oil waste in the asphalt pavement industry and its performance from 2009 to 2022.The VOS viewer application was used to conduct the sciento-metric study analysis.The relationship between interactions detected in co-authored country studies cited sources of co-citation,and the keyword of the co-occurrence and publication source enabled the identification of the research gap.According to the systematic literature review,40%–60% POC can be used to fine aggregate for optimal performance,while 0–100%PKS can be used to replace coarse aggregate.In addition,50%–80% POFA or POC fine(POCF)can be used as a filler replacement,5%–8% POCF or POFA as a bitumen modifier,and 0.3% POF as a stabilizing additive.Furthermore,the study demonstrates that the safety of utilizing wastes with more than 50% CO_(2) emissions can be curtailed with minimal heavy metal leaching and radioactivity levels.The scientometric analysis may encourage researchers to seek out gaps in the literature that will aid in the long-term,multifaceted use of palm oil wastes in the asphalt pavement industry.Furthermore,the study recommends employing and researching the enormous potential of using palm oil waste in the pavement sectors because they are more sustainable and have better performance.However,there are some barriers to using palm oil waste in the asphalt pavement industry,such as a lack of design standards and guidelines,inefficient raw material pro-cessing conversion facilities,and large-scale production equipment.