This report describes the development of a simple engineering model for film cooling. This model is used to derive a relationship between local wall temperature variations and key cooling performance parameters like local heat transfer coefficients and film effectiveness. This relation and method new and different from previously published models. The scope of this report includes the derivation of regression model equations for a flat plate with and without film cooling. The model equation for a flat plate without film cooling can be used to estimate local heat transfer coefficients using surface temperatures measured from infrared thermography. The model equation for the flat plate with film cooling can be used to estimate film cooling effectiveness, η_f, and heat transfer augmentation from the film cooling jet(s).

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The co-gasification of coal and biomass at poly-generation facilities can generate hydrogen rich syngas for producing chemicals, fuels and energy with zero or negative carbon emissions. Here, we present the first carbon capture pilot plant data using physical solvent absorption of CO2 from blended coal and biomass derived syngas. We provide experimental results of the major and minor species in the syngas, sweet gas, and acid gas entering or exiting the pilot-scale pre-combustion CO2 capture absorption column, including experimental data of the accumulation of minor organic and inorganic species across the set of 15 different blends of coal and biomass.

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Rotating Detonation Engines (RDEs) show significant promise for enhancing the efficiency of gas turbine engines while maintaining low 𝑁𝑂𝑥 emissions. This work investigates the predictability of wave modes in a water-cooled RDE under varying operational conditions. Experimental data comprising over 6,700 samples was collected, including parameters such as flow rates, temperatures, pressures, and equivalence ratios. A machine learning approach using the XGBoost library was used to build a multi-class classifier, predicting wave modes based on these inputs. The model achieved a high accuracy of 97%, demonstrating that wave modes are not random but deterministic based on the process conditions. SHAP analysis was used to identify the most influential parameters affecting wave mode prediction. The results show that for the water-cooled NETL RDE, wave mode is determinant and predictable based on the process parameters.

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