Demonstrating the waste heat recovery potential of rotary sinter coolers in iron production facilities is critical for improving energy efficiency and reducing environmental impacts. In this study, numerical analyses were performed for the rotary cooler, and the system’s waste heat recovery capacity was optimized. The effects of particle size, porosity ratio, and inlet air temperature on system performance were examined in detail. Considering two different air outlet regions, the relationships between temperature profiles, cooling efficiency, and pressure loss were evaluated. The findings indicate that there is significant waste heat potential in high-temperature regions and that the system’s energy performance can be improved by recovering this energy. Furthermore, it was found that porosity and particle diameter have decisive effects on both heat transfer and pressure loss. For example, increasing the porosity ratio from 0.3 to 0.5 resulted in a 26% decrease in outlet air temperature and an 82.5% decrease in pressure drop. Similarly, increasing the particle diameter from 0.04 m to 0.08 m reduced the outlet temperature in one region by 11.2 K and the pressure loss by approximately 45%.

This study presents ChemEqT, a computational tool that integrates both Gibbs free energy minimization and the element potential method within a unified framework for determining chemical equilibrium compositions and adiabatic flame temperatures in multicomponent fuel–air gas mixtures. ChemEqT is designed to simplify the complexity of equilibrium combustion calculations and provides users with flexibility in selecting the numerical strategy best suited to their system. The performance of ChemEqT is validated through three case studies involving propane–air and methane–air mixtures. In the first case, simulations of a propane–air system involving 10 species yielded adiabatic flame temperature predictions with a maximum deviation of 0.32% and molar species deviations below 0.77% for CO₂. The second case examines methane–air mixtures enriched with hydrogen, using 52 species, where the maximum deviation was under 0.04%. The third case involves adiabtic flame temperature predictions for 10 different fuel–air mixtures, with deviations below 0.146% for C₃H₆–air. These results establish ChemEqT as a reliable and efficient tool for equilibrium-based combustion analysis, with strong potential for integration into broader energy process simulation frameworks. Its accuracy, modularity, and computational efficiency make it a valuable asset for researchers working in the fields of combustion and energy systems.

The accurate computation of the thermophysical properties of gases and gas mixtures is critical for combustion analysis but remains challenging due to the precision and numerical stability required across wide temperature ranges. In this study, we present Thermophy, a computational framework based on Chebyshev polynomial fitting, developed to calculate thermal conductivity, viscosity, and binary diffusion coefficients for pure gases and multicomponent mixtures. Unlike conventional tools that rely on low-order polynomial approximations, Thermophy applies Chebyshev fitting over defined temperature intervals, enabling higher accuracy, improved numerical stability, and computational efficiency. Thermophy is validated through four case studies involving pure gases, binary mixtures, and ternary mixtures relevant to combustion applications. For pure gases and air, deviations in thermal conductivity and viscosity were found to be 1.22–4.25% and 0.11–4.71%, respectively. For ternary mixtures, viscosity deviations ranged from 0.11 to 0.24%, while binary mixtures showed deviations of 2.60% and 0.20% for viscosity and thermal conductivity, respectively. Binary diffusion coefficients exhibited an overall deviation of approximately 3.35%. The combination of flexible input handling, extensibility, and high-fidelity calculations positions Thermophy as a robust and efficient alternative for integration into combustion modeling and other gas-phase simulation frameworks, including gasification, pyrolysis, global carbon cycle analysis, environmental systems, and fire modeling.

Accurate and efficient modeling of laminar premixed flames is essential for chemical mechanism validation and parametric studies in combustion science. For this purpose, CombF was developed—a semi-analytical computational framework for one-dimensional (1D) laminar premixed flames—offering flexible control over nodal distributions and optional incorporation of experimental temperature data. Unlike conventional fully coupled solvers, CombF explicitly separates the initialization and solution stages, enabling structured control over intermediate structure and temperature constraints while preserving physical consistency. The methodology employs linear interpolation between pre- and post-reaction equilibrium states, adaptive grid refinement, and finite-difference solutions of species and energy conservation equations, with radiation heat transfer optionally included. CombF was validated for ethylene–air premixed flames by comparison with experimental data under varying equivalence ratios and inlet velocities using the YARC-AF kinetic mechanism, and for methane–air premixed flames by additional benchmark comparisons with Cantera, employing the DRM22 mechanism. CombF predictions were further validated against methane and propane–air flames under varying inlet compositions and velocities using the Diego mechanism and evaluated using the curve matching (CM) score, L₂ norms, and phase shift alignment via a nonparametric bootstrap approach. The results demonstrate strong agreement for major species (CO₂, H₂O), while intermediate species (CO, CH₂O) show higher sensitivity to temperature profile choice and nodal resolution, providing a more discriminating assessment of model fidelity. Incorporating experimental temperature fields substantially improves species distribution accuracy and structural alignment. Thus, CombF provides a reliable, flexible, and experimentally adaptive framework that is capable of accurately capturing flame structures, offering a practical tool for preliminary analyses, parametric exploration, and instructional applications in combustion research.