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NASA NTRS2013

Copper-Multiwall Carbon Nanotubes and Copper-Diamond Composites for Advanced Rocket Engines

This paper reports on the research effort to improve the thermal conductivity of the copper-based alloy NARloy-Z (Cu-3 wt.%Ag-0.5 wt.% Zr), the state-of-the-art alloy used to make combustion chamber liners in regeneratively-cooled liquid rocket engines, using nanotechnology. The approach was to embed high thermal conductivity multiwall carbon nanotubes (MWCNTs) and diamond (D) particles in the NARloy-Z matrix using powder metallurgy techniques. The thermal conductivity of MWCNTs and D have been reported to be 5 to 10 times that of NARloy-Z. Hence, 10 to 20 vol. % MWCNT finely dispersed in NARloy-Z matrix could nearly double the thermal conductivity, provided there is a good thermal bond between MWCNTs and copper matrix. Quantum mechanics-based modeling showed that zirconium (Zr) in NARloy-Z should form ZrC at the MWCNT-Cu interface and provide a good thermal bond. In this study, NARloy-Z powder was blended with MWCNTs in a ball mill, and the resulting mixture was consolidated under high pressure and temperature using Field Assisted Sintering Technology (FAST). Microstructural analysis showed that the MWCNTs, which were provided as tangles of MWCNTs by the manufacturer, did not detangle well during blending and formed clumps at the prior particle boundaries. The composites made form these powders showed lower thermal conductivity than the base NARloy-Z. To eliminate the observed physical agglomeration, tangled multiwall MWCNTs were separated by acid treatment and electroless plated with a thin layer of chromium to keep them separated during further processing. Separately, the thermal conductivities of MWCNTs used in this work were measured, and the results showed very low values, a major factor in the low thermal conductivity of the composite. On the other hand, D particles embedded in NARloy-Z matrix showed much improved thermal conductivity. Elemental analysis showed migration of Zr to the NARloy-Z-D interface to form ZrC, which appeared to provide a low contact thermal resistance. These results are consistent with the quantum mechanics-based model predictions. NARloy-Z-D composites have relatively high thermal conductivities and are promising for further development.

Bhat, Biliyar N.↗

NASA NTRS2013

Copper Multiwall Carbon Nanotubes and Copper-Diamond Composites for Advanced Rocket Engines

This paper reports on the research effort to improve the thermal conductivity of the copper-based alloy NARloy-Z (Cu-3 wt.%Ag-0.5 wt.% Zr), the state-of-the-art alloy used to make combustion chamber liners in regeneratively-cooled liquid rocket engines, using nanotechnology. The approach was to embed high thermal conductivity multiwall carbon nanotubes (MWCNTs) and diamond (D) particles in the NARloy-Z matrix using powder metallurgy techniques. The thermal conductivity of MWCNTs and D have been reported to be 5 to 10 times that of NARloy-Z. Hence, 10 to 20 vol. % MWCNT finely dispersed in NARloy-Z matrix could nearly double the thermal conductivity, provided there is a good thermal bond between MWCNTs and copper matrix. Quantum mechanics-based modeling showed that zirconium (Zr) in NARloy-Z should form ZrC at the MWCNT-Cu interface and provide a good thermal bond. In this study, NARloy-Z powder was blended with MWCNTs in a ball mill, and the resulting mixture was consolidated under high pressure and temperature using Field Assisted Sintering Technology (FAST). Microstructural analysis showed that the MWCNTs, which were provided as tangles of MWCNTs by the manufacturer, did not detangle well during blending and formed clumps at the prior particle boundaries. The composites made form these powders showed lower thermal conductivity than the base NARloy-Z. To eliminate the observed physical agglomeration, tangled multiwall MWCNTs were separated by acid treatment and electroless plated with a thin layer of chromium to keep them separated during further processing. Separately, the thermal conductivities of MWCNTs used in this work were measured, and the results showed very low values, a major factor in the low thermal conductivity of the composite. On the other hand, D particles embedded in NARloy-Z matrix showed much improved thermal conductivity. Elemental analysis showed migration of Zr to the NARloy-Z-D interface to form ZrC, which appeared to provide a low contact thermal resistance. These results are consistent with the quantum mechanics-based model predictions. NARloy-Z-D composites have relatively high thermal conductivities and are promising for further development.

Bhat, Biliyar N.↗

NASA NTRS2011

Model-Based Diagnostics for Propellant Loading Systems

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Daigle, Matthew John↗