Sand-casting is one of the most widely used cost-effective manufacturing techniques to produce metal components for various industries. Constantly evolving environmental regulations have increased the necessity for circular and sustainable manufacturing practices. During the casting process, the mold and core undergo a thermal shock when they come in contact with the molten metal. This triggers a severe reaction due to the evaporation of volatiles and the decomposition of chemical binders. This phenomenon can cause defects such as blow-holes and pinholes, leading to increased scrap. The heat removed from the solidifying melt due to these generated gases also affects the cast component by influencing the mechanical properties. From an ecological perspective, some of the gases generated from the decomposing binders have been identified as environmentally hazardous. Studying the gas generation and transport phenomena during the sand-casting process becomes essential in this context.

In this work, the phenomena that affect heat and mass transport due to the generated gases are studied with the help of newly developed experimental techniques in combination with porous material characterization tools. Combining the experimental data with thermal analysis techniques, a computational model for the heat and mass transport in the foundry core is also developed.

The permeability of the molds and cores plays a significant role in determining how efficiently these gases are transported. The permeability and gas volume affect the pressure build-up and defect formation mechanisms of the mold and core. Traditional measurement methods used for determining permeability are not scientifically comparable, nor can they be used for computing the flow characteristics of the molds and cores. In this work, a custom-made measurement setup to measure the permeability of molds and cores is presented. Using the setup, the effect of variation in the grain size distribution and the density on the permeability is quantified. The results show that density affects the permeability more than the grain size distribution. The samples investigated were also characterized using mercury intrusion porosimetry and X-ray microtomography to study the pore characteristics and pore network of the samples. The existing models to predict permeability were evaluated using experimentally measured values and the obtained pore characteristics. The most suitable model to predict the permeability of foundry cores was identified. The identified model was modified to be able to predict permeability using process parameters.

The gas generation rate and volume vary depending on the production parameters of the molds and cores. Commercially available simulation tools often use simplified models for binder decomposition and gas generation, resulting in reduced accuracy in predicting phenomena pertaining to the sand-casting processes. In this work, a novel method to quantify the gases generated from foundry sand mixtures where the core/mold is subjected to conditions similar to the actual casting process is presented. Along with accurate gas volume data, simultaneous temperature measurements in the central and lateral parts of the sample enabled accurate estimation of the heat absorption characteristics associated with the binder decomposition and the gas generation.

Additionally, thermogravimetry analysis was performed for the Furan binder with several heating rates to study the decomposition characteristics and kinetics. Several possible reactions were identified, and the kinetic parameters for each identified reaction during binder decomposition were computed using the integral method. Using the obtained gas transport properties and the kinetic parameters of the binder decomposition and assuming a local thermal non-equilibrium model for heat transport in the porous material, a computational model was developed for the gas generation and transport process in foundry sand cores/molds. The developed model has been validated to a certain extent based on the experimentally obtained gas volume data. The results of the simulation show that the developed model accurately predicts the rate and volume of gases generated and the pressure build-up in the cores.