Reactivity and Hypergolicity of Liquid and Solid Fuels with Mixed Oxides of Nitrogen
2019-12-05T17:10:07Z (GMT) by
When combined with common fuel binders, solid hypergolic fuels can simplify the overall complexity of hybrid rocket systems, as the fuel grain can be ignited and reignited without an external power source or external fluid. In addition, with the hypergolic additive embedded in the binder, the flame zone can be placed at the surface of the grain itself, thereby providing heat to the fuel, improving fuel regression rate, and combustion stability and sustainability. Coupled with high grades of mixed oxides of nitrogen (MON), such hypergolically ignited hybrid configurations are considered a potential propulsion system for a robotic Mars Ascent Vehicle (MAV). Use of the fuel additives and a suitable choice of oxidizer allows for low temperature stability and operation of the propellants, making it an appealing candidate for a simple and storable hybrid propulsion system.
The first half of this work is dedicated to a very application based study of paraffin based hypergolic hybrids, while the second half of this work, independent from the first, focuses on how theory could help in developing future hypergolic propulsion systems.
The process undertaken to develop a paraffin based hypergolic hybrid relied heavily on experimental testing of a wide variety of additive loaded fuels with MON to optimize hybrid motor grain parameters with the goals of minimizing ignition delay, improving combustion stability, and promoting sustainment of the flame. MON 3 and MON 25 (3 wt.% or 25 wt.% nitric oxide mixed with nitrogen tetroxide) were used as oxidizers. Through an initial screening process, we selected two solid hypergolic propellants, sodium amide and potassium bis(trimethylsilyl)amide (PBTSA), as additives to promote hypergolic ignition given their low ignition delays with both grades of MON. Iterations on the grain configuration consisted in minimizing the additive loading to simplify the casting process and increase performance, without losing hypergolicity of the grain or hampering combustion sustainability. Using a 90 wt.% hypergolic additive front segment, we were able to light the grain three times using the hypergolic reaction between the additives and MON 3. Once relights achieved, we mainly focused on demonstrating sustained combustion, and determined that, once the front segment depleted, the lack of heat in the system lead the motor to shut down prior to the end of the targeted burn. This led us to add a reactive additive, sodium borohydride, in the main grain, as a way to generate heat in the motor once the front segment was depleted. With the objective of testing relevant conditions for an actual Mars Ascent Vehicle, one of our final tests was done in an altitude chamber, at a 100,000 ft targeted simulated altitude (equivalent to the atmospheric pressure on Mars), with MON 25 as the oxidizer. Using a mixture of sodium amide, PBTSA, and sodium borohydride, we were able to achieve hypergolic ignition in 425 ms (delay to reach 90% of the maximum chamber pressure) at 102,000 ft simulated altitude, for an average chamber pressure of 113 psia.
During testing we determined that an ideal solid additive should exhibit both low ignition delay with the oxidizer considered, to minimize the motor start up time, and a high heat of combustion, to maximize the energy release and therefore maximize performance. However, the lack of data and theoretical understanding of the reactivity of MONs with non hydrazine based fuels made it challenging to find such an ideal solid additive. Historically, screening processes for new fuel candidates, liquids or solids, have followed a “hit or miss” approach, in which potential fuels were selected based on common characteristics with known hypergols, which is the approach we followed during the development of the hypergolic hybrid. A more robust approach, typically used in the biology and chemistry fields, can be used to predict reactivity of chemicals using statistical analysis. A quantitative structure activity relationship (QSAR) analysis is a statistical analysis used to correlate reactivity to selected molecular descriptors, or properties. Using this approach, one can create models, determined during the QSAR analysis, to predict reactivity of fuel candidates, solely based on their properties. Combined with the recent advancements in computational chemistry and computation of properties, this simple approach has the potential to greatly simplify screening processes for new fuel candidates, as experimental data is not needed anymore. With this method, we were able to fit the logarithmic of the minimum ignition delay for 30 different amines using seven molecular descriptors (heat of formation, heat of vaporization, highest occupied molecular orbital, charge on the nitrogen, rotatable bond count, and ovality), for an R2 value of 0.70. While the main motivation behind starting this theoretical work was to optimize for solid additives properties for the hypergolic hybrid configuration described previously, the potential of such model extends to a wider range of propulsion systems (reaction control systems, orbital maneuvering, etc.), and could be expanded to a wider range of oxidizers using machine learning.