The waste production is closely related with human activity. Various approaches have been applied to manage and reduce its increasing volume (Paranjpe et al. 2023). One of the possibilities that comply with the assumptions of circular economy is utilization of wastes in anaerobic digestion (AD) process. This technology is common worldwide and it is recognized as the cost-effective methods of energy generation that also allow for nutrient recovery, as well as effective waste management (Alharbi et al. 2023). The biogas generated within this process is considered as a multifunctional renewable source that might be a promising alternative to the depleting traditional fuels. It finds various applications such as heat and power generation, fuel in automobiles, and substrate in chemical industry (Shitophyta et al. 2022, Pradeshwaran 2024). Typically, biogas contains 50–70% of CH4, 30–50% of CO2, and 1–10% of other trace gases like H2, H2S, CO, N2. Its composition mainly depends on the feedstock characteristics, operational conditions, and adopted technology (Gani et al. 2023, Archana et al. 2024). Considering further application, the priority action should be increasing its volume and methane content. There are several strategies to achieve these goals, including implementing codigestion strategy, adding additional component to the main substrate, introducing trace elements essential in AD, pretreatment strategies, and introducing enzymes and microbial strains to digesters (Zhang et al. 2019). Each method has limits related to the implementation costs, changes in the adopted technology, operator training needs, and additional energy input, which might negatively influence the energy balance of wastewater treatment plants (WWTPs) (Meng et al. 2022). Therefore, recent scientific attention has focused on combining various strategies to achieve intended goals. Moreover, such combinations might allow for an effective utilization of various wastes, the earlier use of which in AD was difficult. Orange waste could be an example of such a substrate. The previous studies indicated that its application in AD resulted in poor process efficiency, mainly due to the presence of limonene, recognized as the main inhibitor of biological activity (Calabro et al. 2020, Bouaita et al. 2022). In this study, the novel concept of implementing solidified carbon dioxide (SCO2) in the anaerobic co-digestion of municipal sewage sludge (SS) and orange peel waste (OPW) has been proposed. This approach may help overcome the disadvantages of the two-component AD of these wastes. Importantly, such studies have not been conducted thus far. However, the recent studies indicated that application of SCO2 to aerobic granular sludge improved biogas and methane yields and also enhanced the kinetics of biogas production (Kazimierowicz et al. 2023 a,b). Importantly, SCO2 might be generated in biogas upgrading technologies (Yousef 2019). Such solution is consistent with the principles of the circular economy and contributes to reducing the carbon footprint of WWTPs.

This paper identifies and describes the parameters of a numerical model generating the microstructure in the integrated heating-remelting-cooling process of steel specimens. The numerical model allows the heating-remelting-cooling process to be simulated comprehensively. The model is based on the Monte Carlo (MC) method and the finite element method (FEM), and works within the entire volume of the steel sample, contrary to previous studies, in which calculations were carried out for selected, relatively small areas. Experimental studies constituting the basis for the identification and description of model parameters such as: probability function, initial number of orientations, number of cells and number of MC steps were carried out using the Gleeble 3800 thermo-mechanical simulator. The use of GPU capabilities improved the performance of the numerical model and significantly reduced the simulation time. Thanks to the significant acceleration of simulation times, it became possible to comprehensively implement a numerical model of the heating-transformation-cooling process in the entire volume of the test sample. The paper is supplemented by results of performance tests of the numerical model and results of simulation tests.