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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Experimental Investigation of Melting and Solidification Processes of Phase Change Material Heat Exchanger

Rapid development and validation of PCM embedded heat exchangers (PCM-HX) concepts warrant a purpose-built test bench. This paper describes a test facility built for testing various PCM-HX configurations and phase change temperatures that will serve to validate the performance of novel PCM-HX designs. The entire test rig is placed in a temperature-controlled environmental chamber. Inside the PCM-HX containers, up to 48 T-type thermocouples can be spatially distributed on and around the tubes depending on the HX type to capture the phase change process over time. In this paper, a straight tube embedded in PCM having a phase change temperature of 37°C in cylindrical containers is tested. The PCM-HX uses water as an in-tube working fluid. Based on the measured data, the energy balance is analyzed, and its temperature distribution is presented. Here, the maximum deviation between the predicted stored energy and the energy stored calculated from experimental measurements is less than 5%.

36 MATERIALS SCIENCE↗

Foam and Unreacted Material Reduction in Magnesium Oxysulfate for SRPPF Waste Solidification

A magnesium oxysulfate (MOS) grout formulation has been proposed to solidify the liquid effluent from the Savannah River Plutonium Processing Facility (SRPPF) Aqueous Recovery System (ARS). This formulation uses a combination of light-burnt MgO, anhydrous MgSO 4 , and dead-burnt MgO resulting in a grout with good mixability and acceptable density. The setting time for the grout is within the operational limits of the SRPPF facility and the leachate pH is ~9.4, which is within the assumed pH range of the brine from the Waste Isolation Pilot Plant (WIPP). When first tested at the 1-gallon small-scale and 55-gallon full-scale, there was a significant foam layer that raised concerns of a nonhomogeneous final form. A nonhomogeneous mixture could have variable density throughout the waste form and therefore allow for unequal shielding. To reduce the potential for unequal shielding in the final form, a series of foam reduction tests were carried out and a final formulation of 28 wt% light burnt MgO, 10 wt% MgSO 4 , and 62 wt% dead burnt MgO was used to remove the foam in under two hours while still maintaining a mix that has an acceptable density, mix time, peak temperature, and set time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Automated path planning for functionally graded materials considering phase stability and solidification behavior: Application to the Mo-Nb-Ta-Ti system

Functionally graded materials have the potential to improve upon monolithic parts by locally tailoring compositions to surrounding environmental conditions. Difficulties arise when designing composition gradients as incompatible materials can result in detrimental phase formation and failure of the gradient joint. As many alloys are multi-component, designing a composition gradient free of detrimental phases is difficult due to the large composition space available to explore. A framework was developed that improves the path planning algorithm and surrogate models with adaptive sampling schemes specific to their problem definition. A cost function was created to minimize a property (such as cracking susceptibility) along a path. This framework was applied to the Mo-Nb-Ta-Ti system as a case study to showcase the efficiency in building the surrogate models and in iterating different optimal compositionally graded paths.

36 MATERIALS SCIENCE↗

Deep operator network surrogate for phase-field modeling of metal grain growth during solidification

A deep operator network (DeepONet) has been constructed that generates accurate representations of phase-field model simulations for evolving two dimensional metal grain morphology growing from melt. These representations serve as lower resolution, computationally efficient stand-ins for quick parameter space exploration of solutions to the the Allen-Cahn equations that dictate the phase-field model simulations. The experimental target for the phase-field model is a uranium casting system cooling a 434 g uranium charge from a maximum temperature of 1400° C at an average rate of 30° C / min , traversing the crystallographic phases of the pure metal. Experimental parameters inform the phase-field model, whose higher resolution computational model solutions are used to train the DeepONet in a given parameter space with the aim of developing a faster, more efficient method for predicting the solidifying metal's microstructure at different potential experimental values. The final DeepONet generates high accuracy, lower resolution predictions with cumulative relative approximation error over all timesteps of less than 0.5%, while ensuring solutions remain within physically feasible ranges. Further, these relative error values are comparable with other state-of-the-art DeepONet models for microstructure evolution, while significantly reducing the amount of training data required. Training a convolutional neural network simultaneously with the DeepONet, enforcing realistic values at the complex metal grain boundaries, and mathematically encoding boundary conditions into the structure of the DeepONet improved prediction accuracy and computational efficiency over a standard DeepONet model.

36 MATERIALS SCIENCE↗