Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative char...Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.展开更多
Metal organic chemical vapor deposition(MOCVD) is a key equipment in the manufacturing of semiconductor optoelectronic devices and microwave devices in industry. Heating system is a vital part of MOCVD. Specific heati...Metal organic chemical vapor deposition(MOCVD) is a key equipment in the manufacturing of semiconductor optoelectronic devices and microwave devices in industry. Heating system is a vital part of MOCVD. Specific heating device and thermal control technology are needed for each new reactor design. By using resistance-wire heating MOCVD reaction chamber model, thermal analysis and structure optimization of the reactor were developed from the vertical position and the distance between coils of the resistance-wire heater. It is indicated that, within a certain range, the average temperature of the graphite susceptor varies linearly with the vertical distance of heater to susceptor, and with the changed distances between the coils; furthermore, single resistance-wire heater should be placed loosely in the internal and tightly in the external. The modulate accuracy of the temperature field approximately equals the change of the average temperature corresponding to the change of the coil position.展开更多
基金supported in part by the Equipment Development Pre-research Project funded by Equipment Development Department,PRC under Grant No.50923010501Fundamental Research Program of Shenyang Institute of Automation(SIA),Chinese Academy of Sciencess under Grant No.355060201。
文摘Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.
基金Projects(61376076,61274026,61377024)supported by the National Natural Science Foundation of ChinaProjects(12C0108,13C321)supported by the Scientific Research Fund of Hunan Provincial Education Department,ChinaProjects(2013FJ2011,2013FJ4232)supported by the Science and Technology Plan of Hunan Province,China
文摘Metal organic chemical vapor deposition(MOCVD) is a key equipment in the manufacturing of semiconductor optoelectronic devices and microwave devices in industry. Heating system is a vital part of MOCVD. Specific heating device and thermal control technology are needed for each new reactor design. By using resistance-wire heating MOCVD reaction chamber model, thermal analysis and structure optimization of the reactor were developed from the vertical position and the distance between coils of the resistance-wire heater. It is indicated that, within a certain range, the average temperature of the graphite susceptor varies linearly with the vertical distance of heater to susceptor, and with the changed distances between the coils; furthermore, single resistance-wire heater should be placed loosely in the internal and tightly in the external. The modulate accuracy of the temperature field approximately equals the change of the average temperature corresponding to the change of the coil position.
