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The road use load should essentially conform to the plan load as stated in the design guidelines. But in reality, the load received by the road is more than standard, so it has the potential to accelerate road damage. This study aims to predict the increase in the value of the International Roughness Index (IRI) and model the increase in value (IRI) due to overload. The approach method used in the analysis is the prediction of an increase in the IRI value due to excess load. The data collection method is carried out on road sections which include IRI values, vehicle load testing, CBR values and environmental conditions. The location of data collection is carried out on BTS Provincial Road. Surabaya City – Legundi. The analysis method for the prediction of the IRI value is the HDM-4 method, while to model the prediction of the increase in the IRI value is used exponential method with various parameters related to the results. The prediction results show that overload affects the increase in the IRI value. From the initial IRI value of 2.37, if the road is traversed by vehicles with standard loads for 20 years, the IRI value increases to 10.42. While the road traveled by overloaded vehicles within 20 years from an IRI value of 2.37 will increase to 16.88. With overload, the IRI value increases very sharply with the exponential model y = 2.3583e0.0982x . While the standard load by generating an exponential model y = 2.3825e0.0739x . From the results of the exponential model, load overload resulted in a significant increase in the IRI value with a growth rate of 0.0982. When compared to normal expenses which only experienced a growth rate of 0.0739. The modeling results show that overload will increase the growth of very high IRI values with the exponential model increase graph. [ABSTRACT FROM AUTHOR]

This paper comprehensively assesses oil palm biomass and coal blends, focusing on evaluating thermodynamic and kinetics parameters. The experimental approach employs thermogravimetric differential thermal analysis (TG–DTA) with varying heating rates of 5, 10, 15, and 20 K min−1. Laboratory tests are conducted on six blended samples of different coal and oil palm biomass ratios. The evaluation encompasses key combustion parameters, including ignition index (Di), burnout index (Db), combustion performance index (S), reactivity (R), flammability index (C), and index of intensity (Hf). Additionally, thermodynamic parameters such as a change in enthalpy (ΔH), change in Gibbs free energy (ΔG), and change in entropy (ΔS) are analyzed. The results demonstrate that the optimal co-combustion material is a blend of 76% low-rank coal, 19% medium-rank coal, and 5% oil palm fronds, identified as L80M20F. This blend exhibits superior combustion performance, as evidenced by the highest values for Di (31.17 × 10–8% min−3), Db (28.91 × 10–11% min−3 K−1), and R (39.18 × 104 mg min−1). Furthermore, it displays the lowest ΔH of 73.11 kJ mol−1 and ΔS of − 0.0452844 J mol−1 K−1, along with the highest ΔG of 179.77 kJ mol−1. The accuracy of these findings is confirmed through verification with the Gram–Charlier peak function, which yields a negligible margin of error. In conclusion, this study provides crucial insights for decision-makers by assessing combustion and thermodynamic parameters of oil palm biomass and coal blends. The L80M20F, identified as the optimum blended fuel, showcases its potential to enhance combustion efficiency and contribute to the energy transition toward net-zero emissions. [ABSTRACT FROM AUTHOR]

Low-rank coal is currently widely used as fuel to cover the increasing needs of boilers. This kind of coal must be upgraded due to its high moisture content to increase its quality. The drying using a fluidized swirl bed has not been studied to reduce the moisture content of Low-Rank Coal. In contrast, the drying kinetic model has never been found. This study used the angle of guide vanes (AGV) 10°, 20°, and 30° to produce swirl flow. Experiments with varying temperatures used temperatures of 40°C, 45°C, and 50°C. The purpose of this work was to determine the drying characteristics, the best-drying kinetics models, the effective moisture diffusion value, SMER, MER, and SEC on swirl fluidized bed drying. The study results show that the Khazaei and Rational drying kinetic model was the most suitable for the two experimental variations. For experiments with varying AGV, the R2 values obtained are 0.9989–0.9992 and 0.9980–0.9983, while for the variable temperature, the values are 0.9990–0.9992 and 0.9983–0.9992 for each model. The research also found that the smaller AGV angle and higher temperature result in a faster drying rate and consume less energy. [ABSTRACT FROM AUTHOR]