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With the increasingly precise and sensitive nature of space payload, the impact and vibration of the on-orbit unlocking process have become more serious. There is a particular need to develop a device to replace the traditional pyrotechnic device for the reliable connection and low-shock separation for space payloads. In this article, according to the demand of low impact and rapid release of space heavy load, an unlocked trigger device based on shape memory alloy fiber was proposed. Based on the material characteristics of shape memory alloy, the theoretical modeling and analysis of the unlocking trigger device were performed. Combined with the constitutive equation of shape memory alloy and typical boundary conditions, the stress-strain-temperature relationship of shape memory alloy fiber under one-dimensional state was deduced and obtained. A comprehensive performance test of the unlocking trigger device was designed and produced based on the requirement of the space application environment, and the response characteristics and actuation characteristics of shape memory alloy actuator were obtained. Based on the design requirements, a development and experimental study of the prototype shape memory alloy unlock trigger device was conducted. The results demonstrate that the unlocking device based on a shape memory alloy fiber designed in this article has fast unlocking response characteristics and good environmental adaptability, which can provide technical support for space applications of large space load and low-impact locking mechanisms.

Energisation of large power transformers may cause significant voltage dips, of which the severity largely depends on a number of parameters, including circuit breaker closing time, transformer core residual flux and core saturation characteristic, and network conditions. Since most of the parameters are of stochastic nature, Monte Carlo simulation was conducted in this study to stochastically assess the voltage dips caused by transformer energisation in a 400 kV grid, using a network model developed and validated against field measurements. A dip frequency pattern was identified over 1000 stochastic runs and it was found to be sensitive to residual flux distribution but insensitive to closing offset time distribution. The probability of reaching the worst case dip magnitude (estimated under the commonly agreed worst energisation condition) was found to be lower than 0.5%; about 80% of the dips are likely to be with magnitudes lower than 0.6 pu of the worst case. Nevertheless, there are dips with magnitudes exceeding the worst case dip magnitude, indicating the inadequacy of deterministic assessment approach by using the commonly agreed worst energisation condition.

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