A fuzzy directions neural network used for fault detection and isolation (FDI) of a liquid rocket engine (LRE) is presented in this paper. Neural network utilizes fuzzy sets as engine fault classes. Each fuzzy set is an aggregate of fuzzy direction bodies. A fuzzy direction body is described by a direction vector, an included angle and two radii. FDI simulation of the turbo-pump fed liquid rocket engine demonstrates the strong qualities of the fuzzy direction neural network.

Solar thermal propulsion is a potential technology in aerospace applications, and it is a significant issue to improve the heat transfer efficiency of the solar thermal thruster. This paper proposes a novel platelet configuration to be used in the heat exchanger core, which is the most important component of solar thermal system. The platelet passage can enhance the heat transfer between the propellant and the hot core heated by the concentrated sunlight. Based on fluid-solid coupled heat transfer method, the paper utilized the platelet heat transfer characteristic to simulate the heat transfer and flow field of the platelet passage.The simulation result shows that the propellant can be heated to the design temperature of 2300K in the platelet passage of the solar thermal propulsion system, and the fluid-solid coupled method can solve the heat transfer in the platelet structure more precisely.

Solar thermal propulsion is a kind of space propulsion technology with great potential applications. Due to the difficulty of hydrogen storage in orbit, ammonia becomes an ideal candidate propellant as its stability and easier storage. In solar thermal propulsion system, the working temperature is usually above 2300K, and in this condition the dissociation of ammonia will occur. Thus, using ammonia as a single component propellant to compute and analysis the performance of thruster is not precise, and the mixture components produced from ammonia dissociation must be taken into account. In this paper a novel heat exchanger configuration with platelet technology is designed, and based on finite-rate chemical reaction method and computational fluid dynamics, the dissociation process of ammonia in the heat exchanger and nozzle is simulated. Then the influence to the specific impulse of the solar thermal propulsion system is comparatively analyzed. The simulation result indicates that the main productions of the dissociation are N2and H2, and the mole fraction of other components is small value that can be neglected. The specific impulse considering dissociation reaction is higher than not considering, so that this research can estimate the performance of solar thermal propulsion with ammonia propellant more precisely.

Based on fuzzy rule sets match method which is a series of fuzzy neural networks, a system framework used for the fault diagnosis is proposed. This fault diagnosis system consists of five parts, including the extraction of fuzzy rules, fuzzy reference rule sets, the fuzzy rule scheduled to detect, the fuzzy match module and the diagnosis logic module. The extraction of fuzzy rules involves two steps: step one adaptively divides the whole space of the trained data into the subspaces in the form of hypersphere, which is expected efficiently to work out the recognition questions in the high dimension space; step two generates a fuzzy rule in each sample subspace and calculates the membership degree of each fuzzy rule. Many fuzzy reference rule sets are produced by the extraction module of fuzzy rules for the offline learning, and a fuzzy rule set to be detected is online formed while the monitoring process is happening. Beliefs estimated from the fuzzy match process of fuzzy rule sets, which indicate the existence of the working classes in the plant, the diagnosis logic module can export fault detection time, fault isolation time, fault type and fault degree. The simulation researches of the fault diagnosis in space propulsion system demonstrate the superior qualities of the fault diagnosis method on the basis of the fuzzy match of the fuzzy rule sets.